These examples illustrate which models, engines, and prediction types are available in censored. As a reminder, in parsnip,
the model type differentiates basic modeling approaches, such as random forests, proportional hazards models, etc.,
the mode denotes in what kind of modeling context it will be used (here, censored regression), and
the computational engine indicates how the model is fit, such as with a specific R package implementation or even methods outside of R like Keras or Stan.
The following examples use the same data set throughout.
bag_tree() models
With the "rpart" engine
We’ll model the survival of lung cancer patients.
## ── Attaching packages ──────────────────────────────── tidymodels 1.2.0 ── ## ✔ broom 1.0.6 ✔ rsample 1.2.1
## ✔ dials 1.2.1 ✔ tibble 3.2.1
## ✔ dplyr 1.1.4 ✔ tidyr 1.3.1
## ✔ infer 1.0.7 ✔ tune 1.2.1
## ✔ modeldata 1.3.0 ✔ workflows 1.1.4
## ✔ parsnip 1.2.1 ✔ workflowsets 1.1.0
## ✔ purrr 1.0.2 ✔ yardstick 1.3.1
## ✔ recipes 1.0.10 ## ── Conflicts ─────────────────────────────────── tidymodels_conflicts() ──
## ✖ purrr::discard() masks scales::discard()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ✖ recipes::step() masks stats::step()
## • Use suppressPackageStartupMessages() to eliminate package startup messages ## Loading required package: survival
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
bt_spec <-
bag_tree(cost_complexity = 0) %>%
set_engine("rpart") %>%
set_mode("censored regression")
bt_spec ## Bagged Decision Tree Model Specification (censored regression)
##
## Main Arguments:
## cost_complexity = 0
## min_n = 2
##
## Computational engine: rpartNow we create the model fit object:
## parsnip model object
##
##
## Bagging survival trees with 25 bootstrap replications
##
## Call: bagging.data.frame(formula = Surv(time, status) ~ ., data = data)The holdout data can be predicted for survival probability at different time points as well as event time.
predict(
bt_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.946
## 2 500 0.333
## 3 1000 0.00496
predict(bt_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 353
## 2 293
## 3 230
## 4 201
## 5 268
boost_tree() models
With the "mboost" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
bt_spec <-
boost_tree(trees = 15) %>%
set_engine("mboost") %>%
set_mode("censored regression")
bt_spec ## Boosted Tree Model Specification (censored regression)
##
## Main Arguments:
## trees = 15
##
## Computational engine: mboostNow we create the model fit object:
## parsnip model object
##
##
## Model-based Boosting
##
## Call:
## mboost::blackboost(formula = formula, data = data, family = family, control = mboost::boost_control(mstop = 15), tree_controls = partykit::ctree_control(teststat = "quadratic", testtype = "Teststatistic", mincriterion = 0, minsplit = 10, minbucket = 4, maxdepth = 2, saveinfo = FALSE))
##
##
## Cox Partial Likelihood
##
## Loss function:
##
## Number of boosting iterations: mstop = 15
## Step size: 0.1
## Offset: 0
## Number of baselearners: 1The holdout data can be predicted for survival probability at different time points as well as the linear predictor.
predict(
bt_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.867
## 2 500 0.294
## 3 1000 0.0441
predict(bt_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 0.0823
## 2 -0.455
## 3 0.0661
## 4 -0.724
## 5 -0.724
decision_tree() models
With the "rpart" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
dt_spec <-
decision_tree(cost_complexity = 0) %>%
set_engine("rpart") %>%
set_mode("censored regression")
dt_spec ## Decision Tree Model Specification (censored regression)
##
## Main Arguments:
## cost_complexity = 0
##
## Computational engine: rpartNow we create the model fit object:
## parsnip model object
##
## $rpart
## n= 162
##
## node), split, n, deviance, yval
## * denotes terminal node
##
## 1) root 162 217.089100 1.0000000
## 2) ph.ecog< 1.5 125 146.610800 0.8606149
## 4) pat.karno>=65 117 134.248900 0.8042241
## 8) sex>=1.5 47 58.371280 0.5920010
## 16) inst>=12.5 16 17.696750 0.3469493 *
## 17) inst< 12.5 31 36.986020 0.7601739
## 34) ph.ecog< 0.5 14 21.869860 0.4765888 *
## 35) ph.ecog>=0.5 17 12.197510 0.9977683 *
## 9) sex< 1.5 70 71.035080 0.9843711
## 18) wt.loss< -0.5 10 7.608541 0.6466464 *
## 19) wt.loss>=-0.5 60 61.204860 1.0855380
## 38) inst< 18.5 51 52.890560 0.9994210
## 76) pat.karno< 85 27 30.835530 0.8204259
## 152) age< 65.5 16 16.499450 0.6396414 *
## 153) age>=65.5 11 12.211210 1.2318540 *
## 77) pat.karno>=85 24 20.327560 1.2436570
## 154) pat.karno>=95 10 6.634957 0.7568023 *
## 155) pat.karno< 95 14 10.631990 1.6387150 *
## 39) inst>=18.5 9 6.360874 1.6566500 *
## 5) pat.karno< 65 8 5.011986 2.2376180 *
## 3) ph.ecog>=1.5 37 59.992750 1.7157640
## 6) wt.loss>=21 10 10.703230 0.6678083 *
## 7) wt.loss< 21 27 29.918520 3.1500170
## 14) sex>=1.5 12 7.395091 1.9066160 *
## 15) sex< 1.5 15 16.563010 4.5917120 *
##
## $survfit
##
## Call: prodlim::prodlim(formula = form, data = data) ## Stratified Kaplan-Meier estimator for the conditional event time survival function ## Discrete predictor variable: rpartFactor (0.34694933272507, 0.47658881486553, 0.639641354557786, 0.646646427745816, 0.667808261569019, 0.756802251840104, 0.997768280401696, 1.23185367065451, 1.638714591616, 1.65664969973098, 1.90661557969861, 2.23761769770399, 4.59171172488878) ##
## Right-censored response of a survival model
##
## No.Observations: 162
##
## Pattern:
## Freq
## event 116
## right.censored 46
##
## $levels
## [1] "0.34694933272507" "0.47658881486553" "0.639641354557786"
## [4] "0.646646427745816" "0.667808261569019" "0.756802251840104"
## [7] "0.997768280401696" "1.23185367065451" "1.638714591616"
## [10] "1.65664969973098" "1.90661557969861" "2.23761769770399"
## [13] "4.59171172488878"
##
## attr(,"class")
## [1] "pecRpart"The holdout data can be predicted for survival probability at different time points as well as event time.
predict(
dt_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.786
## 2 500 0.143
## 3 1000 NA
predict(dt_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 1.64
## 2 2.24
## 3 1.23
## 4 1.91
## 5 1.91
With the "partykit" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
dt_spec <-
decision_tree() %>%
set_engine("partykit") %>%
set_mode("censored regression")
dt_spec ## Decision Tree Model Specification (censored regression)
##
## Computational engine: partykitNow we create the model fit object:
## parsnip model object
##
##
## Model formula:
## Surv(time, status) ~ inst + age + sex + ph.ecog + ph.karno +
## pat.karno + meal.cal + wt.loss
##
## Fitted party:
## [1] root
## | [2] ph.ecog <= 1: 363.000 (n = 125)
## | [3] ph.ecog > 1
## | | [4] wt.loss <= 20
## | | | [5] sex <= 1: 65.000 (n = 15)
## | | | [6] sex > 1: 201.000 (n = 12)
## | | [7] wt.loss > 20: 524.000 (n = 10)
##
## Number of inner nodes: 3
## Number of terminal nodes: 4The holdout data can be predicted for survival probability at different time points as well as event time.
predict(
dt_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.896
## 2 500 0.334
## 3 1000 0.0719
predict(dt_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 363
## 2 363
## 3 363
## 4 201
## 5 201
proportional_hazards() models
With the "survival" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
ph_spec <-
proportional_hazards() %>%
set_engine("survival") %>%
set_mode("censored regression")
ph_spec ## Proportional Hazards Model Specification (censored regression)
##
## Computational engine: survivalNow we create the model fit object:
## parsnip model object
##
## Call:
## survival::coxph(formula = Surv(time, status) ~ ., data = data,
## model = TRUE, x = TRUE)
##
## coef exp(coef) se(coef) z p
## inst -0.0291726 0.9712488 0.0131293 -2.222 0.02629
## age 0.0146341 1.0147417 0.0119705 1.223 0.22151
## sex -0.5977137 0.5500678 0.2051326 -2.914 0.00357
## ph.ecog 0.7507039 2.1184906 0.2536100 2.960 0.00308
## ph.karno 0.0137315 1.0138262 0.0132752 1.034 0.30096
## pat.karno -0.0082098 0.9918238 0.0082560 -0.994 0.32002
## meal.cal -0.0001233 0.9998767 0.0002841 -0.434 0.66435
## wt.loss -0.0188464 0.9813301 0.0082051 -2.297 0.02162
##
## Likelihood ratio test=32.61 on 8 df, p=7.224e-05
## n= 162, number of events= 116The holdout data can be predicted for survival probability at different time points as well as the linear predictor and event time.
predict(
ph_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.903
## 2 500 0.410
## 3 1000 0.0953
predict(ph_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 -0.373
## 2 -1.24
## 3 -0.852
## 4 -1.33
## 5 -1.11
predict(ph_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 448.
## 2 262.
## 3 337.
## 4 246.
## 5 286.
With the "glmnet" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
ph_spec <-
proportional_hazards(penalty = 0.1) %>%
set_engine("glmnet") %>%
set_mode("censored regression")
ph_spec ## Proportional Hazards Model Specification (censored regression)
##
## Main Arguments:
## penalty = 0.1
##
## Computational engine: glmnetNow we create the model fit object:
## parsnip model object
##
##
## Call: glmnet::glmnet(x = data_obj$x, y = data_obj$y, family = "cox", weights = weights, alpha = alpha, lambda = lambda)
##
## Df %Dev Lambda
## 1 0 0.00 0.221000
## 2 1 0.23 0.201400
## 3 2 0.43 0.183500
## 4 2 0.72 0.167200
## 5 2 0.96 0.152300
## 6 2 1.17 0.138800
## 7 2 1.33 0.126500
## 8 3 1.48 0.115200
## 9 4 1.61 0.105000
## 10 4 1.74 0.095660
## 11 5 1.87 0.087160
## 12 6 2.02 0.079420
## 13 6 2.22 0.072370
## 14 6 2.40 0.065940
## 15 6 2.54 0.060080
## 16 6 2.66 0.054740
## 17 6 2.77 0.049880
## 18 6 2.85 0.045450
## 19 6 2.92 0.041410
## 20 6 2.98 0.037730
## 21 7 3.04 0.034380
## 22 7 3.08 0.031330
## 23 7 3.12 0.028540
## 24 7 3.16 0.026010
## 25 7 3.19 0.023700
## 26 7 3.21 0.021590
## 27 8 3.23 0.019670
## 28 8 3.27 0.017930
## 29 8 3.30 0.016330
## 30 8 3.32 0.014880
## 31 8 3.34 0.013560
## 32 8 3.36 0.012360
## 33 8 3.37 0.011260
## 34 8 3.39 0.010260
## 35 8 3.40 0.009346
## 36 8 3.40 0.008516
## 37 8 3.41 0.007760
## 38 8 3.42 0.007070
## 39 8 3.42 0.006442
## 40 8 3.43 0.005870
## 41 8 3.43 0.005348
## 42 8 3.43 0.004873
## 43 8 3.43 0.004440
## 44 8 3.44 0.004046
## 45 8 3.44 0.003686
## 46 8 3.44 0.003359
## 47 8 3.44 0.003061
## 48 8 3.44 0.002789
## 49 8 3.44 0.002541
## 50 8 3.44 0.002315
## The training data has been saved for prediction.The holdout data can be predicted for survival probability at different time points as well as the linear predictor.
predict(
ph_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.874
## 2 500 0.349
## 3 1000 0.0804
predict(ph_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 0.272
## 2 0.0000798
## 3 0.00575
## 4 -0.0211
## 5 -0.00345
rand_forest() models
With the "partykit" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
rf_spec <-
rand_forest(trees = 200) %>%
set_engine("partykit") %>%
set_mode("censored regression")
rf_spec ## Random Forest Model Specification (censored regression)
##
## Main Arguments:
## trees = 200
##
## Computational engine: partykitNow we create the model fit object:
## parsnip model object
##
## $nodes
## $nodes[[1]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V3 <= 64
## | | | | [5] V8 <= 1025 *
## | | | | [6] V8 > 1025 *
## | | | [7] V3 > 64 *
## | | [8] V5 > 1 *
## | [9] V4 > 1
## | | [10] V5 <= 1
## | | | [11] V5 <= 0 *
## | | | [12] V5 > 0 *
## | | [13] V5 > 1 *
##
## $nodes[[2]]
## [1] root
## | [2] V5 <= 0
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V5 > 0
## | | [6] V5 <= 1
## | | | [7] V9 <= 19
## | | | | [8] V4 <= 1
## | | | | | [9] V9 <= 6 *
## | | | | | [10] V9 > 6 *
## | | | | [11] V4 > 1 *
## | | | [12] V9 > 19 *
## | | [13] V5 > 1
## | | | [14] V4 <= 1 *
## | | | [15] V4 > 1 *
##
## $nodes[[3]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V2 <= 5 *
## | | | [5] V2 > 5
## | | | | [6] V6 <= 90 *
## | | | | [7] V6 > 90 *
## | | [8] V5 > 0
## | | | [9] V6 <= 80
## | | | | [10] V7 <= 70 *
## | | | | [11] V7 > 70
## | | | | | [12] V2 <= 10 *
## | | | | | [13] V2 > 10 *
## | | | [14] V6 > 80 *
## | [15] V5 > 1
## | | [16] V6 <= 60 *
## | | [17] V6 > 60 *
##
## $nodes[[4]]
## [1] root
## | [2] V5 <= 0
## | | [3] V7 <= 80 *
## | | [4] V7 > 80 *
## | [5] V5 > 0
## | | [6] V4 <= 1
## | | | [7] V6 <= 80
## | | | | [8] V3 <= 65 *
## | | | | [9] V3 > 65
## | | | | | [10] V9 <= 7 *
## | | | | | [11] V9 > 7 *
## | | | [12] V6 > 80 *
## | | [13] V4 > 1
## | | | [14] V5 <= 1 *
## | | | [15] V5 > 1 *
##
## $nodes[[5]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V6 <= 80
## | | | | [5] V7 <= 80 *
## | | | | [6] V7 > 80 *
## | | | [7] V6 > 80
## | | | | [8] V9 <= 12
## | | | | | [9] V2 <= 11 *
## | | | | | [10] V2 > 11 *
## | | | | [11] V9 > 12 *
## | | [12] V4 > 1
## | | | [13] V3 <= 53 *
## | | | [14] V3 > 53
## | | | | [15] V3 <= 64 *
## | | | | [16] V3 > 64 *
## | [17] V5 > 1
## | | [18] V8 <= 925 *
## | | [19] V8 > 925 *
##
## $nodes[[6]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 80
## | | | [4] V8 <= 613 *
## | | | [5] V8 > 613
## | | | | [6] V2 <= 10 *
## | | | | [7] V2 > 10 *
## | | [8] V6 > 80
## | | | [9] V8 <= 875 *
## | | | [10] V8 > 875
## | | | | [11] V9 <= 2 *
## | | | | [12] V9 > 2 *
## | [13] V4 > 1
## | | [14] V6 <= 70 *
## | | [15] V6 > 70
## | | | [16] V2 <= 11 *
## | | | [17] V2 > 11 *
##
## $nodes[[7]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V3 <= 74
## | | | [5] V7 <= 90
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V7 <= 70 *
## | | | | | [9] V7 > 70
## | | | | | | [10] V9 <= 4 *
## | | | | | | [11] V9 > 4 *
## | | | [12] V7 > 90 *
## | | [13] V3 > 74 *
##
## $nodes[[8]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V4 <= 1
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V4 > 1
## | | | | [8] V9 <= 6 *
## | | | | [9] V9 > 6 *
## | | [10] V3 > 64
## | | | [11] V7 <= 80 *
## | | | [12] V7 > 80 *
## | [13] V5 > 1
## | | [14] V4 <= 1 *
## | | [15] V4 > 1 *
##
## $nodes[[9]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 80
## | | | [4] V9 <= 20
## | | | | [5] V6 <= 70 *
## | | | | [6] V6 > 70 *
## | | | [7] V9 > 20 *
## | | [8] V6 > 80
## | | | [9] V7 <= 80 *
## | | | [10] V7 > 80 *
## | [11] V4 > 1
## | | [12] V7 <= 90
## | | | [13] V9 <= 3 *
## | | | [14] V9 > 3 *
## | | [15] V7 > 90 *
##
## $nodes[[10]]
## [1] root
## | [2] V5 <= 0
## | | [3] V3 <= 64
## | | | [4] V9 <= 3 *
## | | | [5] V9 > 3 *
## | | [6] V3 > 64 *
## | [7] V5 > 0
## | | [8] V9 <= 27
## | | | [9] V5 <= 1
## | | | | [10] V9 <= 14
## | | | | | [11] V4 <= 1 *
## | | | | | [12] V4 > 1 *
## | | | | [13] V9 > 14 *
## | | | [14] V5 > 1 *
## | | [15] V9 > 27 *
##
## $nodes[[11]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 90
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V3 <= 70
## | | | | | [7] V7 <= 80 *
## | | | | | [8] V7 > 80
## | | | | | | [9] V3 <= 61 *
## | | | | | | [10] V3 > 61 *
## | | | | [11] V3 > 70 *
## | | [12] V7 > 90 *
## | [13] V5 > 1
## | | [14] V4 <= 1 *
## | | [15] V4 > 1 *
##
## $nodes[[12]]
## [1] root
## | [2] V2 <= 21
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V6 <= 70 *
## | | | [6] V6 > 70
## | | | | [7] V7 <= 90
## | | | | | [8] V5 <= 0 *
## | | | | | [9] V5 > 0
## | | | | | | [10] V9 <= 14
## | | | | | | | [11] V7 <= 80 *
## | | | | | | | [12] V7 > 80 *
## | | | | | | [13] V9 > 14 *
## | | | | [14] V7 > 90 *
## | [15] V2 > 21 *
##
## $nodes[[13]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V5 <= 0 *
## | | | [6] V5 > 0
## | | | | [7] V3 <= 60 *
## | | | | [8] V3 > 60
## | | | | | [9] V7 <= 70 *
## | | | | | [10] V7 > 70 *
## | [11] V4 > 1
## | | [12] V5 <= 0 *
## | | [13] V5 > 0
## | | | [14] V5 <= 1 *
## | | | [15] V5 > 1 *
##
## $nodes[[14]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V3 <= 53 *
## | | | [5] V3 > 53
## | | | | [6] V9 <= 14
## | | | | | [7] V9 <= 2 *
## | | | | | [8] V9 > 2 *
## | | | | [9] V9 > 14 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V6 <= 80
## | | | [13] V5 <= 1 *
## | | | [14] V5 > 1 *
## | | [15] V6 > 80
## | | | [16] V5 <= 0 *
## | | | [17] V5 > 0 *
##
## $nodes[[15]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V5 <= 1
## | | | [5] V4 <= 1
## | | | | [6] V8 <= 1275
## | | | | | [7] V3 <= 59 *
## | | | | | [8] V3 > 59
## | | | | | | [9] V5 <= 0 *
## | | | | | | [10] V5 > 0 *
## | | | | [11] V8 > 1275 *
## | | | [12] V4 > 1
## | | | | [13] V6 <= 90
## | | | | | [14] V8 <= 875 *
## | | | | | [15] V8 > 875 *
## | | | | [16] V6 > 90 *
## | | [17] V5 > 1 *
##
## $nodes[[16]]
## [1] root
## | [2] V7 <= 60
## | | [3] V9 <= 8 *
## | | [4] V9 > 8 *
## | [5] V7 > 60
## | | [6] V5 <= 1
## | | | [7] V5 <= 0
## | | | | [8] V6 <= 90 *
## | | | | [9] V6 > 90 *
## | | | [10] V5 > 0
## | | | | [11] V4 <= 1
## | | | | | [12] V6 <= 80 *
## | | | | | [13] V6 > 80 *
## | | | | [14] V4 > 1 *
## | | [15] V5 > 1 *
##
## $nodes[[17]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V9 <= 10
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V9 > 10 *
## | | [8] V4 > 1
## | | | [9] V6 <= 80 *
## | | | [10] V6 > 80 *
## | [11] V5 > 1
## | | [12] V9 <= 10 *
## | | [13] V9 > 10 *
##
## $nodes[[18]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 52 *
## | | [4] V3 > 52
## | | | [5] V5 <= 0
## | | | | [6] V6 <= 90 *
## | | | | [7] V6 > 90 *
## | | | [8] V5 > 0
## | | | | [9] V4 <= 1
## | | | | | [10] V3 <= 66 *
## | | | | | [11] V3 > 66 *
## | | | | [12] V4 > 1 *
## | [13] V5 > 1
## | | [14] V9 <= 11 *
## | | [15] V9 > 11 *
##
## $nodes[[19]]
## [1] root
## | [2] V5 <= 0
## | | [3] V9 <= 3 *
## | | [4] V9 > 3 *
## | [5] V5 > 0
## | | [6] V9 <= 27
## | | | [7] V5 <= 1
## | | | | [8] V7 <= 80
## | | | | | [9] V7 <= 70 *
## | | | | | [10] V7 > 70 *
## | | | | [11] V7 > 80 *
## | | | [12] V5 > 1 *
## | | [13] V9 > 27 *
##
## $nodes[[20]]
## [1] root
## | [2] V7 <= 70
## | | [3] V9 <= 24
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70 *
## | | [6] V9 > 24 *
## | [7] V7 > 70
## | | [8] V4 <= 1
## | | | [9] V5 <= 0 *
## | | | [10] V5 > 0
## | | | | [11] V9 <= 1 *
## | | | | [12] V9 > 1 *
## | | [13] V4 > 1
## | | | [14] V7 <= 90 *
## | | | [15] V7 > 90 *
##
## $nodes[[21]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V8 <= 1060
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V8 > 1060
## | | | | [8] V6 <= 90 *
## | | | | [9] V6 > 90 *
## | | [10] V3 > 64
## | | | [11] V7 <= 80 *
## | | | [12] V7 > 80 *
## | [13] V5 > 1
## | | [14] V9 <= 20 *
## | | [15] V9 > 20 *
##
## $nodes[[22]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0
## | | | | [6] V4 <= 1
## | | | | | [7] V9 <= 10 *
## | | | | | [8] V9 > 10 *
## | | | | [9] V4 > 1 *
## | | [10] V3 > 64
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V9 <= 11 *
## | | [15] V9 > 11 *
##
## $nodes[[23]]
## [1] root
## | [2] V4 <= 1
## | | [3] V9 <= 20
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70
## | | | | [6] V2 <= 4 *
## | | | | [7] V2 > 4
## | | | | | [8] V9 <= 5 *
## | | | | | [9] V9 > 5 *
## | | [10] V9 > 20 *
## | [11] V4 > 1
## | | [12] V5 <= 0 *
## | | [13] V5 > 0
## | | | [14] V2 <= 12 *
## | | | [15] V2 > 12 *
##
## $nodes[[24]]
## [1] root
## | [2] V7 <= 60
## | | [3] V9 <= 13 *
## | | [4] V9 > 13 *
## | [5] V7 > 60
## | | [6] V3 <= 64
## | | | [7] V8 <= 1150
## | | | | [8] V8 <= 925
## | | | | | [9] V8 <= 768 *
## | | | | | [10] V8 > 768 *
## | | | | [11] V8 > 925 *
## | | | [12] V8 > 1150 *
## | | [13] V3 > 64
## | | | [14] V7 <= 80 *
## | | | [15] V7 > 80 *
##
## $nodes[[25]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0 *
## | | [8] V5 > 1 *
## | [9] V4 > 1
## | | [10] V9 <= 3 *
## | | [11] V9 > 3 *
##
## $nodes[[26]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V3 <= 64
## | | | | [5] V7 <= 90 *
## | | | | [6] V7 > 90 *
## | | | [7] V3 > 64 *
## | | [8] V5 > 0
## | | | [9] V6 <= 80
## | | | | [10] V2 <= 13
## | | | | | [11] V7 <= 70 *
## | | | | | [12] V7 > 70 *
## | | | | [13] V2 > 13 *
## | | | [14] V6 > 80 *
## | [15] V5 > 1
## | | [16] V9 <= 20 *
## | | [17] V9 > 20 *
##
## $nodes[[27]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V7 <= 80
## | | | | [5] V3 <= 66 *
## | | | | [6] V3 > 66 *
## | | | [7] V7 > 80
## | | | | [8] V8 <= 1025 *
## | | | | [9] V8 > 1025 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V9 <= -1 *
## | | [13] V9 > -1
## | | | [14] V6 <= 70 *
## | | | [15] V6 > 70
## | | | | [16] V7 <= 80 *
## | | | | [17] V7 > 80 *
##
## $nodes[[28]]
## [1] root
## | [2] V7 <= 90
## | | [3] V5 <= 1
## | | | [4] V4 <= 1
## | | | | [5] V8 <= 1225
## | | | | | [6] V8 <= 463 *
## | | | | | [7] V8 > 463
## | | | | | | [8] V6 <= 80 *
## | | | | | | [9] V6 > 80 *
## | | | | [10] V8 > 1225 *
## | | | [11] V4 > 1
## | | | | [12] V9 <= 4 *
## | | | | [13] V9 > 4 *
## | | [14] V5 > 1
## | | | [15] V4 <= 1 *
## | | | [16] V4 > 1 *
## | [17] V7 > 90 *
##
## $nodes[[29]]
## [1] root
## | [2] V7 <= 90
## | | [3] V8 <= 675
## | | | [4] V7 <= 80 *
## | | | [5] V7 > 80 *
## | | [6] V8 > 675
## | | | [7] V7 <= 60 *
## | | | [8] V7 > 60
## | | | | [9] V3 <= 64
## | | | | | [10] V5 <= 0 *
## | | | | | [11] V5 > 0
## | | | | | | [12] V8 <= 975 *
## | | | | | | [13] V8 > 975 *
## | | | | [14] V3 > 64 *
## | [15] V7 > 90 *
##
## $nodes[[30]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V9 <= 18
## | | | [5] V4 <= 1
## | | | | [6] V2 <= 11 *
## | | | | [7] V2 > 11 *
## | | | [8] V4 > 1
## | | | | [9] V6 <= 90
## | | | | | [10] V5 <= 0 *
## | | | | | [11] V5 > 0
## | | | | | | [12] V3 <= 56 *
## | | | | | | [13] V3 > 56 *
## | | | | [14] V6 > 90 *
## | | [15] V9 > 18 *
##
## $nodes[[31]]
## [1] root
## | [2] V7 <= 80
## | | [3] V4 <= 1
## | | | [4] V3 <= 65 *
## | | | [5] V3 > 65 *
## | | [6] V4 > 1
## | | | [7] V2 <= 10 *
## | | | [8] V2 > 10 *
## | [9] V7 > 80
## | | [10] V5 <= 0 *
## | | [11] V5 > 0
## | | | [12] V2 <= 13 *
## | | | [13] V2 > 13 *
##
## $nodes[[32]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V8 <= 575 *
## | | | [5] V8 > 575
## | | | | [6] V2 <= 16
## | | | | | [7] V3 <= 60 *
## | | | | | [8] V3 > 60 *
## | | | | [9] V2 > 16 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V7 <= 80
## | | | [13] V9 <= 3 *
## | | | [14] V9 > 3 *
## | | [15] V7 > 80 *
##
## $nodes[[33]]
## [1] root
## | [2] V6 <= 70
## | | [3] V9 <= 2 *
## | | [4] V9 > 2 *
## | [5] V6 > 70
## | | [6] V9 <= 3
## | | | [7] V4 <= 1 *
## | | | [8] V4 > 1 *
## | | [9] V9 > 3
## | | | [10] V8 <= 575 *
## | | | [11] V8 > 575
## | | | | [12] V7 <= 80 *
## | | | | [13] V7 > 80 *
##
## $nodes[[34]]
## [1] root
## | [2] V2 <= 12
## | | [3] V8 <= 1175
## | | | [4] V7 <= 90
## | | | | [5] V5 <= 1
## | | | | | [6] V3 <= 66 *
## | | | | | [7] V3 > 66 *
## | | | | [8] V5 > 1 *
## | | | [9] V7 > 90 *
## | | [10] V8 > 1175 *
## | [11] V2 > 12
## | | [12] V7 <= 60 *
## | | [13] V7 > 60
## | | | [14] V2 <= 15 *
## | | | [15] V2 > 15
## | | | | [16] V2 <= 21 *
## | | | | [17] V2 > 21 *
##
## $nodes[[35]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 45 *
## | | [4] V3 > 45
## | | | [5] V9 <= 4
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V7 <= 80 *
## | | | | | [9] V7 > 80 *
## | | | [10] V9 > 4
## | | | | [11] V4 <= 1
## | | | | | [12] V5 <= 0 *
## | | | | | [13] V5 > 0
## | | | | | | [14] V2 <= 11 *
## | | | | | | [15] V2 > 11 *
## | | | | [16] V4 > 1 *
## | [17] V5 > 1
## | | [18] V9 <= 10 *
## | | [19] V9 > 10 *
##
## $nodes[[36]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V9 <= 6
## | | | | [5] V2 <= 5 *
## | | | | [6] V2 > 5 *
## | | | [7] V9 > 6 *
## | | [8] V5 > 0
## | | | [9] V4 <= 1
## | | | | [10] V3 <= 59 *
## | | | | [11] V3 > 59
## | | | | | [12] V8 <= 825 *
## | | | | | [13] V8 > 825 *
## | | | [14] V4 > 1 *
## | [15] V5 > 1
## | | [16] V7 <= 60 *
## | | [17] V7 > 60 *
##
## $nodes[[37]]
## [1] root
## | [2] V7 <= 60
## | | [3] V9 <= 12 *
## | | [4] V9 > 12 *
## | [5] V7 > 60
## | | [6] V8 <= 1100
## | | | [7] V4 <= 1
## | | | | [8] V9 <= 20
## | | | | | [9] V6 <= 80 *
## | | | | | [10] V6 > 80 *
## | | | | [11] V9 > 20 *
## | | | [12] V4 > 1
## | | | | [13] V7 <= 80 *
## | | | | [14] V7 > 80 *
## | | [15] V8 > 1100
## | | | [16] V9 <= 2 *
## | | | [17] V9 > 2 *
##
## $nodes[[38]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V5 <= 1
## | | | [5] V4 <= 1
## | | | | [6] V5 <= 0
## | | | | | [7] V9 <= 5 *
## | | | | | [8] V9 > 5 *
## | | | | [9] V5 > 0
## | | | | | [10] V3 <= 63 *
## | | | | | [11] V3 > 63 *
## | | | [12] V4 > 1
## | | | | [13] V9 <= 4 *
## | | | | [14] V9 > 4 *
## | | [15] V5 > 1 *
##
## $nodes[[39]]
## [1] root
## | [2] V7 <= 70
## | | [3] V9 <= 20
## | | | [4] V4 <= 1 *
## | | | [5] V4 > 1 *
## | | [6] V9 > 20 *
## | [7] V7 > 70
## | | [8] V5 <= 0
## | | | [9] V6 <= 90 *
## | | | [10] V6 > 90 *
## | | [11] V5 > 0
## | | | [12] V2 <= 12
## | | | | [13] V6 <= 80
## | | | | | [14] V9 <= 14 *
## | | | | | [15] V9 > 14 *
## | | | | [16] V6 > 80 *
## | | | [17] V2 > 12 *
##
## $nodes[[40]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 90
## | | | [4] V9 <= 4
## | | | | [5] V4 <= 1 *
## | | | | [6] V4 > 1 *
## | | | [7] V9 > 4
## | | | | [8] V4 <= 1
## | | | | | [9] V7 <= 80
## | | | | | | [10] V7 <= 70 *
## | | | | | | [11] V7 > 70 *
## | | | | | [12] V7 > 80 *
## | | | | [13] V4 > 1 *
## | | [14] V7 > 90 *
## | [15] V5 > 1
## | | [16] V3 <= 65 *
## | | [17] V3 > 65 *
##
## $nodes[[41]]
## [1] root
## | [2] V3 <= 67
## | | [3] V6 <= 80
## | | | [4] V3 <= 56 *
## | | | [5] V3 > 56
## | | | | [6] V2 <= 15 *
## | | | | [7] V2 > 15 *
## | | [8] V6 > 80
## | | | [9] V5 <= 0
## | | | | [10] V3 <= 56 *
## | | | | [11] V3 > 56 *
## | | | [12] V5 > 0 *
## | [13] V3 > 67
## | | [14] V9 <= 14
## | | | [15] V6 <= 80
## | | | | [16] V5 <= 1 *
## | | | | [17] V5 > 1 *
## | | | [18] V6 > 80 *
## | | [19] V9 > 14 *
##
## $nodes[[42]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 70
## | | | [4] V5 <= 1
## | | | | [5] V7 <= 70 *
## | | | | [6] V7 > 70
## | | | | | [7] V5 <= 0 *
## | | | | | [8] V5 > 0 *
## | | | [9] V5 > 1 *
## | | [10] V3 > 70 *
## | [11] V4 > 1
## | | [12] V7 <= 70 *
## | | [13] V7 > 70
## | | | [14] V2 <= 12
## | | | | [15] V5 <= 0 *
## | | | | [16] V5 > 0 *
## | | | [17] V2 > 12 *
##
## $nodes[[43]]
## [1] root
## | [2] V5 <= 0
## | | [3] V6 <= 90 *
## | | [4] V6 > 90 *
## | [5] V5 > 0
## | | [6] V4 <= 1
## | | | [7] V2 <= 7
## | | | | [8] V7 <= 60 *
## | | | | [9] V7 > 60 *
## | | | [10] V2 > 7
## | | | | [11] V6 <= 70 *
## | | | | [12] V6 > 70 *
## | | [13] V4 > 1
## | | | [14] V8 <= 675 *
## | | | [15] V8 > 675 *
##
## $nodes[[44]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V6 <= 90 *
## | | | [5] V6 > 90 *
## | | [6] V5 > 0
## | | | [7] V4 <= 1
## | | | | [8] V7 <= 60 *
## | | | | [9] V7 > 60
## | | | | | [10] V6 <= 80 *
## | | | | | [11] V6 > 80 *
## | | | [12] V4 > 1 *
## | [13] V5 > 1
## | | [14] V7 <= 60 *
## | | [15] V7 > 60 *
##
## $nodes[[45]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 67
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V3 <= 57 *
## | | | | | [9] V3 > 57 *
## | | [10] V3 > 67
## | | | [11] V9 <= 10 *
## | | | [12] V9 > 10 *
## | [13] V4 > 1
## | | [14] V5 <= 0 *
## | | [15] V5 > 0
## | | | [16] V9 <= 0 *
## | | | [17] V9 > 0 *
##
## $nodes[[46]]
## [1] root
## | [2] V5 <= 0
## | | [3] V7 <= 90 *
## | | [4] V7 > 90 *
## | [5] V5 > 0
## | | [6] V7 <= 60 *
## | | [7] V7 > 60
## | | | [8] V2 <= 5 *
## | | | [9] V2 > 5
## | | | | [10] V3 <= 59 *
## | | | | [11] V3 > 59
## | | | | | [12] V5 <= 1
## | | | | | | [13] V6 <= 80 *
## | | | | | | [14] V6 > 80 *
## | | | | | [15] V5 > 1 *
##
## $nodes[[47]]
## [1] root
## | [2] V3 <= 64
## | | [3] V8 <= 1175
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0
## | | | | [6] V8 <= 925
## | | | | | [7] V9 <= 14 *
## | | | | | [8] V9 > 14 *
## | | | | [9] V8 > 925 *
## | | [10] V8 > 1175 *
## | [11] V3 > 64
## | | [12] V9 <= 20
## | | | [13] V6 <= 70 *
## | | | [14] V6 > 70
## | | | | [15] V5 <= 0 *
## | | | | [16] V5 > 0 *
## | | [17] V9 > 20 *
##
## $nodes[[48]]
## [1] root
## | [2] V6 <= 70
## | | [3] V7 <= 60 *
## | | [4] V7 > 60 *
## | [5] V6 > 70
## | | [6] V4 <= 1
## | | | [7] V3 <= 65
## | | | | [8] V7 <= 80 *
## | | | | [9] V7 > 80 *
## | | | [10] V3 > 65 *
## | | [11] V4 > 1
## | | | [12] V5 <= 0 *
## | | | [13] V5 > 0 *
##
## $nodes[[49]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 70 *
## | | [4] V7 > 70
## | | | [5] V9 <= 12
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80
## | | | | | [8] V5 <= 0
## | | | | | | [9] V3 <= 51 *
## | | | | | | [10] V3 > 51 *
## | | | | | [11] V5 > 0 *
## | | | [12] V9 > 12 *
## | [13] V5 > 1
## | | [14] V9 <= 20 *
## | | [15] V9 > 20 *
##
## $nodes[[50]]
## [1] root
## | [2] V7 <= 70
## | | [3] V4 <= 1
## | | | [4] V9 <= 20
## | | | | [5] V6 <= 70 *
## | | | | [6] V6 > 70 *
## | | | [7] V9 > 20 *
## | | [8] V4 > 1 *
## | [9] V7 > 70
## | | [10] V3 <= 63
## | | | [11] V4 <= 1
## | | | | [12] V5 <= 0 *
## | | | | [13] V5 > 0 *
## | | | [14] V4 > 1 *
## | | [15] V3 > 63
## | | | [16] V9 <= 3 *
## | | | [17] V9 > 3 *
##
## $nodes[[51]]
## [1] root
## | [2] V7 <= 70
## | | [3] V9 <= 20
## | | | [4] V2 <= 3 *
## | | | [5] V2 > 3 *
## | | [6] V9 > 20 *
## | [7] V7 > 70
## | | [8] V3 <= 63
## | | | [9] V4 <= 1 *
## | | | [10] V4 > 1 *
## | | [11] V3 > 63
## | | | [12] V8 <= 1100
## | | | | [13] V4 <= 1 *
## | | | | [14] V4 > 1 *
## | | | [15] V8 > 1100 *
##
## $nodes[[52]]
## [1] root
## | [2] V6 <= 70
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V6 > 70
## | | [6] V5 <= 0
## | | | [7] V3 <= 63
## | | | | [8] V8 <= 768 *
## | | | | [9] V8 > 768 *
## | | | [10] V3 > 63 *
## | | [11] V5 > 0
## | | | [12] V4 <= 1
## | | | | [13] V8 <= 825 *
## | | | | [14] V8 > 825 *
## | | | [15] V4 > 1
## | | | | [16] V3 <= 63 *
## | | | | [17] V3 > 63 *
##
## $nodes[[53]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V4 <= 1
## | | | [5] V5 <= 1
## | | | | [6] V3 <= 65
## | | | | | [7] V5 <= 0 *
## | | | | | [8] V5 > 0
## | | | | | | [9] V3 <= 53 *
## | | | | | | [10] V3 > 53 *
## | | | | [11] V3 > 65 *
## | | | [12] V5 > 1 *
## | | [13] V4 > 1
## | | | [14] V7 <= 80 *
## | | | [15] V7 > 80 *
##
## $nodes[[54]]
## [1] root
## | [2] V3 <= 45 *
## | [3] V3 > 45
## | | [4] V7 <= 70
## | | | [5] V2 <= 3 *
## | | | [6] V2 > 3
## | | | | [7] V9 <= 13
## | | | | | [8] V8 <= 1025 *
## | | | | | [9] V8 > 1025 *
## | | | | [10] V9 > 13 *
## | | [11] V7 > 70
## | | | [12] V5 <= 0 *
## | | | [13] V5 > 0
## | | | | [14] V4 <= 1
## | | | | | [15] V7 <= 90 *
## | | | | | [16] V7 > 90 *
## | | | | [17] V4 > 1 *
##
## $nodes[[55]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V7 <= 80
## | | | [5] V8 <= 538 *
## | | | [6] V8 > 538
## | | | | [7] V6 <= 80 *
## | | | | [8] V6 > 80 *
## | | [9] V7 > 80
## | | | [10] V2 <= 10
## | | | | [11] V7 <= 90 *
## | | | | [12] V7 > 90 *
## | | | [13] V2 > 10
## | | | | [14] V4 <= 1 *
## | | | | [15] V4 > 1 *
##
## $nodes[[56]]
## [1] root
## | [2] V5 <= 0
## | | [3] V7 <= 80 *
## | | [4] V7 > 80 *
## | [5] V5 > 0
## | | [6] V2 <= 10
## | | | [7] V5 <= 1 *
## | | | [8] V5 > 1 *
## | | [9] V2 > 10
## | | | [10] V9 <= 20
## | | | | [11] V7 <= 80 *
## | | | | [12] V7 > 80 *
## | | | [13] V9 > 20 *
##
## $nodes[[57]]
## [1] root
## | [2] V3 <= 48 *
## | [3] V3 > 48
## | | [4] V7 <= 80
## | | | [5] V5 <= 0 *
## | | | [6] V5 > 0
## | | | | [7] V3 <= 63 *
## | | | | [8] V3 > 63
## | | | | | [9] V9 <= 20 *
## | | | | | [10] V9 > 20 *
## | | [11] V7 > 80
## | | | [12] V5 <= 0 *
## | | | [13] V5 > 0
## | | | | [14] V7 <= 90 *
## | | | | [15] V7 > 90 *
##
## $nodes[[58]]
## [1] root
## | [2] V3 <= 44 *
## | [3] V3 > 44
## | | [4] V4 <= 1
## | | | [5] V7 <= 60 *
## | | | [6] V7 > 60
## | | | | [7] V2 <= 11
## | | | | | [8] V3 <= 64 *
## | | | | | [9] V3 > 64 *
## | | | | [10] V2 > 11
## | | | | | [11] V9 <= 5 *
## | | | | | [12] V9 > 5 *
## | | [13] V4 > 1
## | | | [14] V5 <= 1
## | | | | [15] V2 <= 12 *
## | | | | [16] V2 > 12 *
## | | | [17] V5 > 1 *
##
## $nodes[[59]]
## [1] root
## | [2] V8 <= 488 *
## | [3] V8 > 488
## | | [4] V5 <= 0
## | | | [5] V4 <= 1 *
## | | | [6] V4 > 1 *
## | | [7] V5 > 0
## | | | [8] V9 <= 20
## | | | | [9] V8 <= 1100
## | | | | | [10] V5 <= 1
## | | | | | | [11] V2 <= 12 *
## | | | | | | [12] V2 > 12 *
## | | | | | [13] V5 > 1 *
## | | | | [14] V8 > 1100 *
## | | | [15] V9 > 20 *
##
## $nodes[[60]]
## [1] root
## | [2] V6 <= 80
## | | [3] V9 <= 20
## | | | [4] V5 <= 1
## | | | | [5] V7 <= 80 *
## | | | | [6] V7 > 80 *
## | | | [7] V5 > 1 *
## | | [8] V9 > 20 *
## | [9] V6 > 80
## | | [10] V4 <= 1
## | | | [11] V2 <= 13
## | | | | [12] V9 <= 5 *
## | | | | [13] V9 > 5 *
## | | | [14] V2 > 13 *
## | | [15] V4 > 1 *
##
## $nodes[[61]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V8 <= 1039 *
## | | | | [7] V8 > 1039 *
## | | [8] V4 > 1
## | | | [9] V6 <= 80 *
## | | | [10] V6 > 80
## | | | | [11] V9 <= 2 *
## | | | | [12] V9 > 2 *
## | [13] V5 > 1
## | | [14] V9 <= 10 *
## | | [15] V9 > 10 *
##
## $nodes[[62]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 63
## | | | [4] V8 <= 1025
## | | | | [5] V4 <= 1 *
## | | | | [6] V4 > 1 *
## | | | [7] V8 > 1025
## | | | | [8] V2 <= 5 *
## | | | | [9] V2 > 5 *
## | | [10] V3 > 63
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V2 <= 5 *
## | | [15] V2 > 5 *
##
## $nodes[[63]]
## [1] root
## | [2] V4 <= 1
## | | [3] V8 <= 910
## | | | [4] V9 <= 20 *
## | | | [5] V9 > 20 *
## | | [6] V8 > 910
## | | | [7] V8 <= 1225
## | | | | [8] V5 <= 0 *
## | | | | [9] V5 > 0 *
## | | | [10] V8 > 1225 *
## | [11] V4 > 1
## | | [12] V8 <= 825
## | | | [13] V6 <= 80 *
## | | | [14] V6 > 80 *
## | | [15] V8 > 825
## | | | [16] V5 <= 0 *
## | | | [17] V5 > 0 *
##
## $nodes[[64]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 65
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0 *
## | | [6] V3 > 65
## | | | [7] V8 <= 925 *
## | | | [8] V8 > 925 *
## | [9] V4 > 1
## | | [10] V5 <= 1
## | | | [11] V7 <= 80 *
## | | | [12] V7 > 80 *
## | | [13] V5 > 1 *
##
## $nodes[[65]]
## [1] root
## | [2] V5 <= 0
## | | [3] V6 <= 90 *
## | | [4] V6 > 90 *
## | [5] V5 > 0
## | | [6] V5 <= 1
## | | | [7] V4 <= 1
## | | | | [8] V9 <= 2 *
## | | | | [9] V9 > 2 *
## | | | [10] V4 > 1
## | | | | [11] V8 <= 825 *
## | | | | [12] V8 > 825 *
## | | [13] V5 > 1
## | | | [14] V8 <= 925 *
## | | | [15] V8 > 925 *
##
## $nodes[[66]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V4 <= 1
## | | | [5] V8 <= 730 *
## | | | [6] V8 > 730
## | | | | [7] V6 <= 80 *
## | | | | [8] V6 > 80
## | | | | | [9] V2 <= 13 *
## | | | | | [10] V2 > 13 *
## | | [11] V4 > 1
## | | | [12] V3 <= 54 *
## | | | [13] V3 > 54
## | | | | [14] V2 <= 10 *
## | | | | [15] V2 > 10 *
##
## $nodes[[67]]
## [1] root
## | [2] V3 <= 71
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V4 <= 1
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80
## | | | | | [8] V5 <= 0 *
## | | | | | [9] V5 > 0 *
## | | | [10] V4 > 1
## | | | | [11] V2 <= 12 *
## | | | | [12] V2 > 12 *
## | [13] V3 > 71 *
##
## $nodes[[68]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 80
## | | | [4] V3 <= 69
## | | | | [5] V2 <= 13 *
## | | | | [6] V2 > 13 *
## | | | [7] V3 > 69 *
## | | [8] V6 > 80
## | | | [9] V2 <= 13
## | | | | [10] V2 <= 6 *
## | | | | [11] V2 > 6 *
## | | | [12] V2 > 13 *
## | [13] V4 > 1
## | | [14] V8 <= 1060
## | | | [15] V6 <= 80 *
## | | | [16] V6 > 80 *
## | | [17] V8 > 1060 *
##
## $nodes[[69]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V2 <= 6 *
## | | | [6] V2 > 6
## | | | | [7] V3 <= 63 *
## | | | | [8] V3 > 63 *
## | [9] V4 > 1
## | | [10] V7 <= 90
## | | | [11] V9 <= 0 *
## | | | [12] V9 > 0
## | | | | [13] V5 <= 1 *
## | | | | [14] V5 > 1 *
## | | [15] V7 > 90 *
##
## $nodes[[70]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 71
## | | | [4] V9 <= 20
## | | | | [5] V6 <= 90
## | | | | | [6] V8 <= 1125
## | | | | | | [7] V9 <= 7 *
## | | | | | | [8] V9 > 7 *
## | | | | | [9] V8 > 1125 *
## | | | | [10] V6 > 90 *
## | | | [11] V9 > 20 *
## | | [12] V3 > 71 *
## | [13] V4 > 1
## | | [14] V5 <= 0 *
## | | [15] V5 > 0
## | | | [16] V2 <= 12 *
## | | | [17] V2 > 12 *
##
## $nodes[[71]]
## [1] root
## | [2] V5 <= 0
## | | [3] V3 <= 64
## | | | [4] V7 <= 90 *
## | | | [5] V7 > 90 *
## | | [6] V3 > 64 *
## | [7] V5 > 0
## | | [8] V7 <= 60 *
## | | [9] V7 > 60
## | | | [10] V4 <= 1
## | | | | [11] V9 <= 20
## | | | | | [12] V8 <= 1025 *
## | | | | | [13] V8 > 1025 *
## | | | | [14] V9 > 20 *
## | | | [15] V4 > 1
## | | | | [16] V2 <= 12 *
## | | | | [17] V2 > 12 *
##
## $nodes[[72]]
## [1] root
## | [2] V7 <= 70
## | | [3] V2 <= 3 *
## | | [4] V2 > 3
## | | | [5] V4 <= 1 *
## | | | [6] V4 > 1 *
## | [7] V7 > 70
## | | [8] V5 <= 0
## | | | [9] V7 <= 90 *
## | | | [10] V7 > 90 *
## | | [11] V5 > 0
## | | | [12] V4 <= 1
## | | | | [13] V3 <= 59 *
## | | | | [14] V3 > 59 *
## | | | [15] V4 > 1 *
##
## $nodes[[73]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V6 <= 80
## | | | | [5] V7 <= 80 *
## | | | | [6] V7 > 80 *
## | | | [7] V6 > 80
## | | | | [8] V3 <= 65 *
## | | | | [9] V3 > 65 *
## | | [10] V4 > 1
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V9 <= 11 *
## | | [15] V9 > 11 *
##
## $nodes[[74]]
## [1] root
## | [2] V6 <= 80
## | | [3] V4 <= 1
## | | | [4] V9 <= 20
## | | | | [5] V9 <= 8 *
## | | | | [6] V9 > 8 *
## | | | [7] V9 > 20 *
## | | [8] V4 > 1
## | | | [9] V6 <= 60 *
## | | | [10] V6 > 60 *
## | [11] V6 > 80
## | | [12] V4 <= 1
## | | | [13] V9 <= 5 *
## | | | [14] V9 > 5 *
## | | [15] V4 > 1 *
##
## $nodes[[75]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0
## | | | | [6] V9 <= 14
## | | | | | [7] V7 <= 80 *
## | | | | | [8] V7 > 80 *
## | | | | [9] V9 > 14 *
## | | [10] V4 > 1
## | | | [11] V9 <= 10 *
## | | | [12] V9 > 10 *
## | [13] V5 > 1
## | | [14] V2 <= 13 *
## | | [15] V2 > 13 *
##
## $nodes[[76]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V3 <= 64
## | | | [5] V6 <= 80 *
## | | | [6] V6 > 80
## | | | | [7] V2 <= 13 *
## | | | | [8] V2 > 13 *
## | | [9] V3 > 64
## | | | [10] V8 <= 575 *
## | | | [11] V8 > 575
## | | | | [12] V8 <= 910 *
## | | | | [13] V8 > 910
## | | | | | [14] V8 <= 1100 *
## | | | | | [15] V8 > 1100 *
##
## $nodes[[77]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V5 <= 1
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V8 <= 825 *
## | | | | | [9] V8 > 825
## | | | | | | [10] V7 <= 80 *
## | | | | | | [11] V7 > 80 *
## | | | [12] V5 > 1 *
## | [13] V4 > 1
## | | [14] V9 <= -1 *
## | | [15] V9 > -1
## | | | [16] V7 <= 80 *
## | | | [17] V7 > 80 *
##
## $nodes[[78]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V3 <= 68
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80
## | | | | | [8] V7 <= 80 *
## | | | | | [9] V7 > 80 *
## | | | [10] V3 > 68 *
## | [11] V4 > 1
## | | [12] V9 <= -1 *
## | | [13] V9 > -1
## | | | [14] V6 <= 70 *
## | | | [15] V6 > 70
## | | | | [16] V8 <= 925 *
## | | | | [17] V8 > 925 *
##
## $nodes[[79]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V8 <= 463 *
## | | | [5] V8 > 463
## | | | | [6] V7 <= 80 *
## | | | | [7] V7 > 80 *
## | | [8] V5 > 0
## | | | [9] V6 <= 80
## | | | | [10] V9 <= 0 *
## | | | | [11] V9 > 0
## | | | | | [12] V3 <= 66 *
## | | | | | [13] V3 > 66 *
## | | | [14] V6 > 80
## | | | | [15] V4 <= 1 *
## | | | | [16] V4 > 1 *
## | [17] V5 > 1
## | | [18] V4 <= 1 *
## | | [19] V4 > 1 *
##
## $nodes[[80]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 90
## | | | [4] V6 <= 80
## | | | | [5] V2 <= 11 *
## | | | | [6] V2 > 11 *
## | | | [7] V6 > 80
## | | | | [8] V7 <= 80 *
## | | | | [9] V7 > 80 *
## | | [10] V7 > 90 *
## | [11] V5 > 1
## | | [12] V2 <= 13 *
## | | [13] V2 > 13 *
##
## $nodes[[81]]
## [1] root
## | [2] V5 <= 0
## | | [3] V2 <= 11 *
## | | [4] V2 > 11 *
## | [5] V5 > 0
## | | [6] V4 <= 1
## | | | [7] V9 <= 20
## | | | | [8] V6 <= 70 *
## | | | | [9] V6 > 70
## | | | | | [10] V9 <= 8 *
## | | | | | [11] V9 > 8 *
## | | | [12] V9 > 20 *
## | | [13] V4 > 1
## | | | [14] V9 <= 10 *
## | | | [15] V9 > 10 *
##
## $nodes[[82]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V3 <= 65
## | | | | [5] V9 <= 1 *
## | | | | [6] V9 > 1
## | | | | | [7] V2 <= 4 *
## | | | | | [8] V2 > 4 *
## | | | [9] V3 > 65
## | | | | [10] V6 <= 80 *
## | | | | [11] V6 > 80 *
## | | [12] V4 > 1
## | | | [13] V7 <= 80 *
## | | | [14] V7 > 80 *
## | [15] V5 > 1
## | | [16] V9 <= 20 *
## | | [17] V9 > 20 *
##
## $nodes[[83]]
## [1] root
## | [2] V3 <= 70
## | | [3] V8 <= 925
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0
## | | | | [6] V2 <= 6 *
## | | | | [7] V2 > 6 *
## | | [8] V8 > 925
## | | | [9] V4 <= 1
## | | | | [10] V8 <= 1025 *
## | | | | [11] V8 > 1025 *
## | | | [12] V4 > 1 *
## | [13] V3 > 70 *
##
## $nodes[[84]]
## [1] root
## | [2] V5 <= 0
## | | [3] V2 <= 12
## | | | [4] V9 <= 3 *
## | | | [5] V9 > 3 *
## | | [6] V2 > 12 *
## | [7] V5 > 0
## | | [8] V3 <= 50 *
## | | [9] V3 > 50
## | | | [10] V5 <= 1
## | | | | [11] V2 <= 13
## | | | | | [12] V9 <= 14 *
## | | | | | [13] V9 > 14 *
## | | | | [14] V2 > 13 *
## | | | [15] V5 > 1
## | | | | [16] V2 <= 13 *
## | | | | [17] V2 > 13 *
##
## $nodes[[85]]
## [1] root
## | [2] V7 <= 60
## | | [3] V9 <= 13 *
## | | [4] V9 > 13 *
## | [5] V7 > 60
## | | [6] V6 <= 70 *
## | | [7] V6 > 70
## | | | [8] V2 <= 13
## | | | | [9] V5 <= 0 *
## | | | | [10] V5 > 0
## | | | | | [11] V9 <= 13 *
## | | | | | [12] V9 > 13 *
## | | | [13] V2 > 13 *
##
## $nodes[[86]]
## [1] root
## | [2] V4 <= 1
## | | [3] V9 <= 2 *
## | | [4] V9 > 2
## | | | [5] V3 <= 70
## | | | | [6] V6 <= 80
## | | | | | [7] V3 <= 62 *
## | | | | | [8] V3 > 62 *
## | | | | [9] V6 > 80 *
## | | | [10] V3 > 70 *
## | [11] V4 > 1
## | | [12] V7 <= 90
## | | | [13] V2 <= 12
## | | | | [14] V2 <= 3 *
## | | | | [15] V2 > 3 *
## | | | [16] V2 > 12 *
## | | [17] V7 > 90 *
##
## $nodes[[87]]
## [1] root
## | [2] V7 <= 60
## | | [3] V9 <= 14 *
## | | [4] V9 > 14 *
## | [5] V7 > 60
## | | [6] V5 <= 1
## | | | [7] V9 <= 5
## | | | | [8] V6 <= 80 *
## | | | | [9] V6 > 80
## | | | | | [10] V7 <= 80 *
## | | | | | [11] V7 > 80
## | | | | | | [12] V5 <= 0 *
## | | | | | | [13] V5 > 0 *
## | | | [14] V9 > 5
## | | | | [15] V4 <= 1 *
## | | | | [16] V4 > 1 *
## | | [17] V5 > 1 *
##
## $nodes[[88]]
## [1] root
## | [2] V4 <= 1
## | | [3] V8 <= 875
## | | | [4] V3 <= 64 *
## | | | [5] V3 > 64 *
## | | [6] V8 > 875
## | | | [7] V7 <= 70 *
## | | | [8] V7 > 70
## | | | | [9] V5 <= 0 *
## | | | | [10] V5 > 0 *
## | [11] V4 > 1
## | | [12] V6 <= 70 *
## | | [13] V6 > 70
## | | | [14] V9 <= 3 *
## | | | [15] V9 > 3 *
##
## $nodes[[89]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V2 <= 16
## | | | | [6] V8 <= 575 *
## | | | | [7] V8 > 575
## | | | | | [8] V5 <= 0 *
## | | | | | [9] V5 > 0 *
## | | | [10] V2 > 16 *
## | [11] V4 > 1
## | | [12] V6 <= 70 *
## | | [13] V6 > 70
## | | | [14] V9 <= 14
## | | | | [15] V2 <= 5 *
## | | | | [16] V2 > 5 *
## | | | [17] V9 > 14 *
##
## $nodes[[90]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V8 <= 1275
## | | | | [6] V5 <= 1
## | | | | | [7] V6 <= 80 *
## | | | | | [8] V6 > 80 *
## | | | | [9] V5 > 1 *
## | | | [10] V8 > 1275 *
## | [11] V4 > 1
## | | [12] V6 <= 70 *
## | | [13] V6 > 70
## | | | [14] V7 <= 80 *
## | | | [15] V7 > 80 *
##
## $nodes[[91]]
## [1] root
## | [2] V7 <= 70
## | | [3] V7 <= 60 *
## | | [4] V7 > 60 *
## | [5] V7 > 70
## | | [6] V4 <= 1
## | | | [7] V5 <= 0 *
## | | | [8] V5 > 0
## | | | | [9] V7 <= 80 *
## | | | | [10] V7 > 80 *
## | | [11] V4 > 1
## | | | [12] V7 <= 80 *
## | | | [13] V7 > 80 *
##
## $nodes[[92]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 70 *
## | | [4] V7 > 70
## | | | [5] V4 <= 1
## | | | | [6] V9 <= 5 *
## | | | | [7] V9 > 5 *
## | | | [8] V4 > 1
## | | | | [9] V2 <= 12
## | | | | | [10] V3 <= 64 *
## | | | | | [11] V3 > 64 *
## | | | | [12] V2 > 12 *
## | [13] V5 > 1
## | | [14] V9 <= 11 *
## | | [15] V9 > 11 *
##
## $nodes[[93]]
## [1] root
## | [2] V3 <= 51 *
## | [3] V3 > 51
## | | [4] V4 <= 1
## | | | [5] V7 <= 80
## | | | | [6] V3 <= 65 *
## | | | | [7] V3 > 65
## | | | | | [8] V9 <= 17 *
## | | | | | [9] V9 > 17 *
## | | | [10] V7 > 80
## | | | | [11] V8 <= 993 *
## | | | | [12] V8 > 993 *
## | | [13] V4 > 1
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0
## | | | | [16] V3 <= 60 *
## | | | | [17] V3 > 60 *
##
## $nodes[[94]]
## [1] root
## | [2] V5 <= 1
## | | [3] V9 <= 12
## | | | [4] V5 <= 0
## | | | | [5] V4 <= 1 *
## | | | | [6] V4 > 1 *
## | | | [7] V5 > 0
## | | | | [8] V4 <= 1 *
## | | | | [9] V4 > 1 *
## | | [10] V9 > 12
## | | | [11] V4 <= 1 *
## | | | [12] V4 > 1 *
## | [13] V5 > 1
## | | [14] V7 <= 60 *
## | | [15] V7 > 60 *
##
## $nodes[[95]]
## [1] root
## | [2] V3 <= 46 *
## | [3] V3 > 46
## | | [4] V7 <= 60
## | | | [5] V9 <= 13 *
## | | | [6] V9 > 13 *
## | | [7] V7 > 60
## | | | [8] V6 <= 70 *
## | | | [9] V6 > 70
## | | | | [10] V3 <= 63
## | | | | | [11] V5 <= 0 *
## | | | | | [12] V5 > 0 *
## | | | | [13] V3 > 63
## | | | | | [14] V8 <= 993 *
## | | | | | [15] V8 > 993 *
##
## $nodes[[96]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V3 <= 64
## | | | [5] V9 <= 3
## | | | | [6] V9 <= -1 *
## | | | | [7] V9 > -1 *
## | | | [8] V9 > 3
## | | | | [9] V5 <= 0 *
## | | | | [10] V5 > 0 *
## | | [11] V3 > 64
## | | | [12] V5 <= 1
## | | | | [13] V3 <= 68 *
## | | | | [14] V3 > 68 *
## | | | [15] V5 > 1 *
##
## $nodes[[97]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V9 <= 24
## | | | | [6] V6 <= 70 *
## | | | | [7] V6 > 70 *
## | | | [8] V9 > 24 *
## | [9] V4 > 1
## | | [10] V5 <= 1
## | | | [11] V9 <= 2 *
## | | | [12] V9 > 2 *
## | | [13] V5 > 1 *
##
## $nodes[[98]]
## [1] root
## | [2] V7 <= 90
## | | [3] V5 <= 1
## | | | [4] V9 <= 2
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V9 > 2
## | | | | [8] V8 <= 1175
## | | | | | [9] V6 <= 80 *
## | | | | | [10] V6 > 80 *
## | | | | [11] V8 > 1175 *
## | | [12] V5 > 1
## | | | [13] V9 <= 20 *
## | | | [14] V9 > 20 *
## | [15] V7 > 90 *
##
## $nodes[[99]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V8 <= 925
## | | | | [6] V8 <= 513 *
## | | | | [7] V8 > 513 *
## | | | [8] V8 > 925
## | | | | [9] V3 <= 68
## | | | | | [10] V2 <= 12 *
## | | | | | [11] V2 > 12 *
## | | | | [12] V3 > 68 *
## | [13] V4 > 1
## | | [14] V6 <= 80
## | | | [15] V2 <= 13 *
## | | | [16] V2 > 13 *
## | | [17] V6 > 80 *
##
## $nodes[[100]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V5 <= 0 *
## | | | [6] V5 > 0
## | | | | [7] V8 <= 993 *
## | | | | [8] V8 > 993
## | | | | | [9] V5 <= 1 *
## | | | | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V9 <= 14
## | | | [13] V6 <= 80 *
## | | | [14] V6 > 80 *
## | | [15] V9 > 14 *
##
## $nodes[[101]]
## [1] root
## | [2] V8 <= 488
## | | [3] V9 <= 20 *
## | | [4] V9 > 20 *
## | [5] V8 > 488
## | | [6] V5 <= 0
## | | | [7] V4 <= 1 *
## | | | [8] V4 > 1 *
## | | [9] V5 > 0
## | | | [10] V7 <= 80
## | | | | [11] V6 <= 80
## | | | | | [12] V3 <= 56 *
## | | | | | [13] V3 > 56
## | | | | | | [14] V3 <= 65 *
## | | | | | | [15] V3 > 65 *
## | | | | [16] V6 > 80 *
## | | | [17] V7 > 80
## | | | | [18] V8 <= 910 *
## | | | | [19] V8 > 910 *
##
## $nodes[[102]]
## [1] root
## | [2] V6 <= 70
## | | [3] V2 <= 13 *
## | | [4] V2 > 13 *
## | [5] V6 > 70
## | | [6] V7 <= 90
## | | | [7] V4 <= 1
## | | | | [8] V3 <= 59 *
## | | | | [9] V3 > 59
## | | | | | [10] V5 <= 0 *
## | | | | | [11] V5 > 0 *
## | | | [12] V4 > 1
## | | | | [13] V3 <= 62 *
## | | | | [14] V3 > 62 *
## | | [15] V7 > 90 *
##
## $nodes[[103]]
## [1] root
## | [2] V6 <= 70
## | | [3] V7 <= 60 *
## | | [4] V7 > 60 *
## | [5] V6 > 70
## | | [6] V4 <= 1
## | | | [7] V3 <= 60 *
## | | | [8] V3 > 60
## | | | | [9] V7 <= 70 *
## | | | | [10] V7 > 70 *
## | | [11] V4 > 1
## | | | [12] V6 <= 80 *
## | | | [13] V6 > 80 *
##
## $nodes[[104]]
## [1] root
## | [2] V5 <= 0
## | | [3] V8 <= 463 *
## | | [4] V8 > 463
## | | | [5] V4 <= 1 *
## | | | [6] V4 > 1 *
## | [7] V5 > 0
## | | [8] V4 <= 1
## | | | [9] V3 <= 71
## | | | | [10] V2 <= 15
## | | | | | [11] V9 <= 17
## | | | | | | [12] V9 <= 1 *
## | | | | | | [13] V9 > 1 *
## | | | | | [14] V9 > 17 *
## | | | | [15] V2 > 15 *
## | | | [16] V3 > 71 *
## | | [17] V4 > 1
## | | | [18] V5 <= 1 *
## | | | [19] V5 > 1 *
##
## $nodes[[105]]
## [1] root
## | [2] V6 <= 70
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V6 > 70
## | | [6] V5 <= 0
## | | | [7] V2 <= 13
## | | | | [8] V8 <= 725 *
## | | | | [9] V8 > 725 *
## | | | [10] V2 > 13 *
## | | [11] V5 > 0
## | | | [12] V8 <= 588 *
## | | | [13] V8 > 588
## | | | | [14] V7 <= 70 *
## | | | | [15] V7 > 70
## | | | | | [16] V3 <= 64 *
## | | | | | [17] V3 > 64 *
##
## $nodes[[106]]
## [1] root
## | [2] V2 <= 12
## | | [3] V6 <= 90
## | | | [4] V2 <= 2 *
## | | | [5] V2 > 2
## | | | | [6] V3 <= 59 *
## | | | | [7] V3 > 59
## | | | | | [8] V4 <= 1 *
## | | | | | [9] V4 > 1 *
## | | [10] V6 > 90 *
## | [11] V2 > 12
## | | [12] V2 <= 16 *
## | | [13] V2 > 16 *
##
## $nodes[[107]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V9 <= 8
## | | | | | [7] V5 <= 0 *
## | | | | | [8] V5 > 0 *
## | | | | [9] V9 > 8 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V9 <= -2 *
## | | [13] V9 > -2
## | | | [14] V6 <= 80 *
## | | | [15] V6 > 80 *
##
## $nodes[[108]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V9 <= 1 *
## | | | [5] V9 > 1
## | | | | [6] V2 <= 11
## | | | | | [7] V7 <= 80 *
## | | | | | [8] V7 > 80 *
## | | | | [9] V2 > 11 *
## | | [10] V4 > 1
## | | | [11] V8 <= 538 *
## | | | [12] V8 > 538
## | | | | [13] V9 <= 0 *
## | | | | [14] V9 > 0 *
## | [15] V5 > 1 *
##
## $nodes[[109]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V9 <= 5
## | | | | [6] V3 <= 63 *
## | | | | [7] V3 > 63 *
## | | | [8] V9 > 5
## | | | | [9] V8 <= 1100
## | | | | | [10] V9 <= 14 *
## | | | | | [11] V9 > 14 *
## | | | | [12] V8 > 1100 *
## | [13] V4 > 1
## | | [14] V6 <= 80 *
## | | [15] V6 > 80 *
##
## $nodes[[110]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 71
## | | | [4] V5 <= 1
## | | | | [5] V2 <= 16
## | | | | | [6] V7 <= 80
## | | | | | | [7] V9 <= 5 *
## | | | | | | [8] V9 > 5 *
## | | | | | [9] V7 > 80 *
## | | | | [10] V2 > 16 *
## | | | [11] V5 > 1 *
## | | [12] V3 > 71 *
## | [13] V4 > 1
## | | [14] V7 <= 80
## | | | [15] V5 <= 1 *
## | | | [16] V5 > 1 *
## | | [17] V7 > 80 *
##
## $nodes[[111]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V7 <= 90
## | | | | [6] V9 <= 14
## | | | | | [7] V8 <= 1175
## | | | | | | [8] V9 <= 5 *
## | | | | | | [9] V9 > 5 *
## | | | | | [10] V8 > 1175 *
## | | | | [11] V9 > 14 *
## | | | [12] V7 > 90 *
## | [13] V4 > 1
## | | [14] V9 <= 2 *
## | | [15] V9 > 2
## | | | [16] V2 <= 12 *
## | | | [17] V2 > 12 *
##
## $nodes[[112]]
## [1] root
## | [2] V5 <= 0
## | | [3] V9 <= 6 *
## | | [4] V9 > 6 *
## | [5] V5 > 0
## | | [6] V9 <= 27
## | | | [7] V5 <= 1
## | | | | [8] V4 <= 1
## | | | | | [9] V2 <= 11 *
## | | | | | [10] V2 > 11 *
## | | | | [11] V4 > 1 *
## | | | [12] V5 > 1 *
## | | [13] V9 > 27 *
##
## $nodes[[113]]
## [1] root
## | [2] V5 <= 1
## | | [3] V9 <= 5
## | | | [4] V6 <= 80 *
## | | | [5] V6 > 80
## | | | | [6] V6 <= 90 *
## | | | | [7] V6 > 90 *
## | | [8] V9 > 5
## | | | [9] V3 <= 64
## | | | | [10] V7 <= 80 *
## | | | | [11] V7 > 80 *
## | | | [12] V3 > 64 *
## | [13] V5 > 1
## | | [14] V4 <= 1 *
## | | [15] V4 > 1 *
##
## $nodes[[114]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V8 <= 925
## | | | | [6] V3 <= 64 *
## | | | | [7] V3 > 64 *
## | | | [8] V8 > 925
## | | | | [9] V5 <= 0 *
## | | | | [10] V5 > 0 *
## | [11] V4 > 1
## | | [12] V7 <= 80 *
## | | [13] V7 > 80
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0 *
##
## $nodes[[115]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V7 <= 90
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0
## | | | | | [7] V3 <= 53 *
## | | | | | [8] V3 > 53 *
## | | | [9] V7 > 90 *
## | | [10] V3 > 64
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V6 <= 60 *
## | | [15] V6 > 60 *
##
## $nodes[[116]]
## [1] root
## | [2] V4 <= 1
## | | [3] V8 <= 1275
## | | | [4] V5 <= 1
## | | | | [5] V9 <= 11
## | | | | | [6] V5 <= 0 *
## | | | | | [7] V5 > 0 *
## | | | | [8] V9 > 11 *
## | | | [9] V5 > 1 *
## | | [10] V8 > 1275 *
## | [11] V4 > 1
## | | [12] V2 <= 11 *
## | | [13] V2 > 11 *
##
## $nodes[[117]]
## [1] root
## | [2] V6 <= 80
## | | [3] V9 <= 27
## | | | [4] V9 <= 1 *
## | | | [5] V9 > 1
## | | | | [6] V5 <= 1 *
## | | | | [7] V5 > 1 *
## | | [8] V9 > 27 *
## | [9] V6 > 80
## | | [10] V3 <= 64
## | | | [11] V4 <= 1 *
## | | | [12] V4 > 1 *
## | | [13] V3 > 64 *
##
## $nodes[[118]]
## [1] root
## | [2] V3 <= 45 *
## | [3] V3 > 45
## | | [4] V5 <= 1
## | | | [5] V2 <= 1 *
## | | | [6] V2 > 1
## | | | | [7] V7 <= 90
## | | | | | [8] V3 <= 66
## | | | | | | [9] V5 <= 0 *
## | | | | | | [10] V5 > 0 *
## | | | | | [11] V3 > 66 *
## | | | | [12] V7 > 90 *
## | | [13] V5 > 1
## | | | [14] V2 <= 13 *
## | | | [15] V2 > 13 *
##
## $nodes[[119]]
## [1] root
## | [2] V3 <= 64
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V3 <= 50 *
## | | | [6] V3 > 50
## | | | | [7] V8 <= 768 *
## | | | | [8] V8 > 768
## | | | | | [9] V9 <= 5 *
## | | | | | [10] V9 > 5 *
## | [11] V3 > 64
## | | [12] V2 <= 5 *
## | | [13] V2 > 5
## | | | [14] V8 <= 875 *
## | | | [15] V8 > 875
## | | | | [16] V2 <= 15 *
## | | | | [17] V2 > 15 *
##
## $nodes[[120]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80 *
## | | [8] V4 > 1
## | | | [9] V9 <= 1 *
## | | | [10] V9 > 1 *
## | [11] V5 > 1
## | | [12] V8 <= 910 *
## | | [13] V8 > 910 *
##
## $nodes[[121]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V7 <= 90
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0
## | | | | | [7] V7 <= 70 *
## | | | | | [8] V7 > 70 *
## | | | [9] V7 > 90 *
## | | [10] V4 > 1
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V4 <= 1 *
## | | [15] V4 > 1 *
##
## $nodes[[122]]
## [1] root
## | [2] V6 <= 70
## | | [3] V5 <= 1 *
## | | [4] V5 > 1 *
## | [5] V6 > 70
## | | [6] V7 <= 70 *
## | | [7] V7 > 70
## | | | [8] V3 <= 64
## | | | | [9] V2 <= 12
## | | | | | [10] V9 <= 1 *
## | | | | | [11] V9 > 1 *
## | | | | [12] V2 > 12 *
## | | | [13] V3 > 64
## | | | | [14] V8 <= 1030 *
## | | | | [15] V8 > 1030 *
##
## $nodes[[123]]
## [1] root
## | [2] V5 <= 0
## | | [3] V3 <= 60 *
## | | [4] V3 > 60 *
## | [5] V5 > 0
## | | [6] V6 <= 70
## | | | [7] V2 <= 13 *
## | | | [8] V2 > 13 *
## | | [9] V6 > 70
## | | | [10] V7 <= 90
## | | | | [11] V3 <= 54 *
## | | | | [12] V3 > 54
## | | | | | [13] V4 <= 1 *
## | | | | | [14] V4 > 1 *
## | | | [15] V7 > 90 *
##
## $nodes[[124]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V5 <= 1
## | | | | [6] V3 <= 63 *
## | | | | [7] V3 > 63 *
## | | | [8] V5 > 1 *
## | [9] V4 > 1
## | | [10] V6 <= 60 *
## | | [11] V6 > 60
## | | | [12] V3 <= 64
## | | | | [13] V3 <= 58 *
## | | | | [14] V3 > 58 *
## | | | [15] V3 > 64 *
##
## $nodes[[125]]
## [1] root
## | [2] V7 <= 70
## | | [3] V9 <= 24
## | | | [4] V4 <= 1
## | | | | [5] V5 <= 1 *
## | | | | [6] V5 > 1 *
## | | | [7] V4 > 1 *
## | | [8] V9 > 24 *
## | [9] V7 > 70
## | | [10] V4 <= 1
## | | | [11] V9 <= 6
## | | | | [12] V5 <= 0 *
## | | | | [13] V5 > 0 *
## | | | [14] V9 > 6 *
## | | [15] V4 > 1
## | | | [16] V7 <= 90
## | | | | [17] V2 <= 12 *
## | | | | [18] V2 > 12 *
## | | | [19] V7 > 90 *
##
## $nodes[[126]]
## [1] root
## | [2] V7 <= 70
## | | [3] V2 <= 3 *
## | | [4] V2 > 3
## | | | [5] V3 <= 63 *
## | | | [6] V3 > 63
## | | | | [7] V9 <= 11 *
## | | | | [8] V9 > 11 *
## | [9] V7 > 70
## | | [10] V7 <= 90
## | | | [11] V9 <= 6
## | | | | [12] V6 <= 80 *
## | | | | [13] V6 > 80 *
## | | | [14] V9 > 6
## | | | | [15] V6 <= 80 *
## | | | | [16] V6 > 80 *
## | | [17] V7 > 90 *
##
## $nodes[[127]]
## [1] root
## | [2] V5 <= 1
## | | [3] V6 <= 80
## | | | [4] V7 <= 80 *
## | | | [5] V7 > 80 *
## | | [6] V6 > 80
## | | | [7] V4 <= 1
## | | | | [8] V8 <= 875 *
## | | | | [9] V8 > 875
## | | | | | [10] V2 <= 13 *
## | | | | | [11] V2 > 13 *
## | | | [12] V4 > 1
## | | | | [13] V3 <= 58 *
## | | | | [14] V3 > 58 *
## | [15] V5 > 1
## | | [16] V2 <= 12 *
## | | [17] V2 > 12 *
##
## $nodes[[128]]
## [1] root
## | [2] V3 <= 45 *
## | [3] V3 > 45
## | | [4] V6 <= 80
## | | | [5] V4 <= 1
## | | | | [6] V9 <= 20
## | | | | | [7] V6 <= 70 *
## | | | | | [8] V6 > 70 *
## | | | | [9] V9 > 20 *
## | | | [10] V4 > 1
## | | | | [11] V6 <= 70 *
## | | | | [12] V6 > 70 *
## | | [13] V6 > 80
## | | | [14] V7 <= 80 *
## | | | [15] V7 > 80
## | | | | [16] V9 <= 3 *
## | | | | [17] V9 > 3 *
##
## $nodes[[129]]
## [1] root
## | [2] V5 <= 0
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V5 > 0
## | | [6] V4 <= 1
## | | | [7] V5 <= 1
## | | | | [8] V7 <= 80
## | | | | | [9] V7 <= 70 *
## | | | | | [10] V7 > 70 *
## | | | | [11] V7 > 80 *
## | | | [12] V5 > 1 *
## | | [13] V4 > 1
## | | | [14] V2 <= 12 *
## | | | [15] V2 > 12 *
##
## $nodes[[130]]
## [1] root
## | [2] V3 <= 47 *
## | [3] V3 > 47
## | | [4] V4 <= 1
## | | | [5] V7 <= 60 *
## | | | [6] V7 > 60
## | | | | [7] V2 <= 16
## | | | | | [8] V8 <= 875 *
## | | | | | [9] V8 > 875
## | | | | | | [10] V7 <= 80 *
## | | | | | | [11] V7 > 80 *
## | | | | [12] V2 > 16 *
## | | [13] V4 > 1
## | | | [14] V6 <= 90
## | | | | [15] V7 <= 80 *
## | | | | [16] V7 > 80 *
## | | | [17] V6 > 90 *
##
## $nodes[[131]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V3 <= 70
## | | | [5] V7 <= 90
## | | | | [6] V5 <= 0
## | | | | | [7] V8 <= 1039 *
## | | | | | [8] V8 > 1039 *
## | | | | [9] V5 > 0
## | | | | | [10] V9 <= 12 *
## | | | | | [11] V9 > 12 *
## | | | [12] V7 > 90 *
## | | [13] V3 > 70 *
##
## $nodes[[132]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V2 <= 4 *
## | | | [6] V2 > 4
## | | | | [7] V3 <= 60 *
## | | | | [8] V3 > 60
## | | | | | [9] V8 <= 1030
## | | | | | | [10] V6 <= 80 *
## | | | | | | [11] V6 > 80 *
## | | | | | [12] V8 > 1030 *
## | [13] V4 > 1
## | | [14] V5 <= 1
## | | | [15] V3 <= 60
## | | | | [16] V6 <= 80 *
## | | | | [17] V6 > 80 *
## | | | [18] V3 > 60 *
## | | [19] V5 > 1 *
##
## $nodes[[133]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V8 <= 1125
## | | | | [5] V9 <= 14
## | | | | | [6] V7 <= 70 *
## | | | | | [7] V7 > 70 *
## | | | | [8] V9 > 14 *
## | | | [9] V8 > 1125 *
## | | [10] V4 > 1
## | | | [11] V7 <= 90
## | | | | [12] V2 <= 12
## | | | | | [13] V8 <= 925 *
## | | | | | [14] V8 > 925 *
## | | | | [15] V2 > 12 *
## | | | [16] V7 > 90 *
## | [17] V5 > 1 *
##
## $nodes[[134]]
## [1] root
## | [2] V6 <= 70
## | | [3] V9 <= 20
## | | | [4] V4 <= 1 *
## | | | [5] V4 > 1 *
## | | [6] V9 > 20 *
## | [7] V6 > 70
## | | [8] V7 <= 70 *
## | | [9] V7 > 70
## | | | [10] V5 <= 0
## | | | | [11] V7 <= 90 *
## | | | | [12] V7 > 90 *
## | | | [13] V5 > 0
## | | | | [14] V7 <= 90
## | | | | | [15] V2 <= 12 *
## | | | | | [16] V2 > 12 *
## | | | | [17] V7 > 90 *
##
## $nodes[[135]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V3 <= 65
## | | | | [5] V2 <= 4 *
## | | | | [6] V2 > 4
## | | | | | [7] V8 <= 1025 *
## | | | | | [8] V8 > 1025 *
## | | | [9] V3 > 65 *
## | | [10] V4 > 1
## | | | [11] V7 <= 80 *
## | | | [12] V7 > 80 *
## | [13] V5 > 1
## | | [14] V2 <= 13
## | | | [15] V8 <= 910 *
## | | | [16] V8 > 910 *
## | | [17] V2 > 13 *
##
## $nodes[[136]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V3 <= 65
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V3 > 65
## | | | | [8] V9 <= 7 *
## | | | | [9] V9 > 7 *
## | | [10] V4 > 1
## | | | [11] V9 <= 0 *
## | | | [12] V9 > 0 *
## | [13] V5 > 1
## | | [14] V2 <= 13 *
## | | [15] V2 > 13 *
##
## $nodes[[137]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 71
## | | | [4] V8 <= 925 *
## | | | [5] V8 > 925
## | | | | [6] V3 <= 53 *
## | | | | [7] V3 > 53
## | | | | | [8] V6 <= 80 *
## | | | | | [9] V6 > 80 *
## | | [10] V3 > 71 *
## | [11] V4 > 1
## | | [12] V7 <= 90
## | | | [13] V2 <= 15
## | | | | [14] V5 <= 0 *
## | | | | [15] V5 > 0 *
## | | | [16] V2 > 15 *
## | | [17] V7 > 90 *
##
## $nodes[[138]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V3 <= 64
## | | | | [5] V9 <= 2 *
## | | | | [6] V9 > 2 *
## | | | [7] V3 > 64 *
## | | [8] V4 > 1
## | | | [9] V2 <= 11 *
## | | | [10] V2 > 11 *
## | [11] V5 > 1
## | | [12] V4 <= 1 *
## | | [13] V4 > 1 *
##
## $nodes[[139]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V3 <= 68
## | | | | [5] V6 <= 80 *
## | | | | [6] V6 > 80
## | | | | | [7] V2 <= 5 *
## | | | | | [8] V2 > 5 *
## | | | [9] V3 > 68 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V9 <= -1 *
## | | [13] V9 > -1
## | | | [14] V7 <= 70 *
## | | | [15] V7 > 70
## | | | | [16] V6 <= 80 *
## | | | | [17] V6 > 80 *
##
## $nodes[[140]]
## [1] root
## | [2] V6 <= 70
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V6 > 70
## | | [6] V3 <= 64
## | | | [7] V2 <= 10
## | | | | [8] V7 <= 80 *
## | | | | [9] V7 > 80 *
## | | | [10] V2 > 10
## | | | | [11] V6 <= 80 *
## | | | | [12] V6 > 80 *
## | | [13] V3 > 64
## | | | [14] V8 <= 1030 *
## | | | [15] V8 > 1030 *
##
## $nodes[[141]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 70 *
## | | [4] V7 > 70
## | | | [5] V4 <= 1
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80
## | | | | | [8] V8 <= 1039 *
## | | | | | [9] V8 > 1039 *
## | | | [10] V4 > 1
## | | | | [11] V3 <= 51 *
## | | | | [12] V3 > 51
## | | | | | [13] V2 <= 6 *
## | | | | | [14] V2 > 6 *
## | [15] V5 > 1
## | | [16] V2 <= 13 *
## | | [17] V2 > 13 *
##
## $nodes[[142]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V7 <= 90
## | | | | [5] V7 <= 70 *
## | | | | [6] V7 > 70
## | | | | | [7] V9 <= 1 *
## | | | | | [8] V9 > 1 *
## | | | [9] V7 > 90 *
## | | [10] V3 > 64
## | | | [11] V5 <= 0 *
## | | | [12] V5 > 0
## | | | | [13] V3 <= 69 *
## | | | | [14] V3 > 69 *
## | [15] V5 > 1
## | | [16] V9 <= 20 *
## | | [17] V9 > 20 *
##
## $nodes[[143]]
## [1] root
## | [2] V6 <= 60 *
## | [3] V6 > 60
## | | [4] V5 <= 1
## | | | [5] V9 <= 8
## | | | | [6] V7 <= 80 *
## | | | | [7] V7 > 80
## | | | | | [8] V6 <= 90
## | | | | | | [9] V8 <= 975 *
## | | | | | | [10] V8 > 975 *
## | | | | | [11] V6 > 90 *
## | | | [12] V9 > 8
## | | | | [13] V4 <= 1
## | | | | | [14] V2 <= 11 *
## | | | | | [15] V2 > 11 *
## | | | | [16] V4 > 1 *
## | | [17] V5 > 1 *
##
## $nodes[[144]]
## [1] root
## | [2] V3 <= 63
## | | [3] V2 <= 10
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0 *
## | | [6] V2 > 10
## | | | [7] V8 <= 1025 *
## | | | [8] V8 > 1025 *
## | [9] V3 > 63
## | | [10] V9 <= 27
## | | | [11] V5 <= 1
## | | | | [12] V5 <= 0 *
## | | | | [13] V5 > 0
## | | | | | [14] V7 <= 70 *
## | | | | | [15] V7 > 70 *
## | | | [16] V5 > 1 *
## | | [17] V9 > 27 *
##
## $nodes[[145]]
## [1] root
## | [2] V6 <= 70
## | | [3] V9 <= 20
## | | | [4] V4 <= 1 *
## | | | [5] V4 > 1 *
## | | [6] V9 > 20 *
## | [7] V6 > 70
## | | [8] V4 <= 1
## | | | [9] V9 <= 6 *
## | | | [10] V9 > 6
## | | | | [11] V7 <= 80 *
## | | | | [12] V7 > 80 *
## | | [13] V4 > 1
## | | | [14] V9 <= 14
## | | | | [15] V2 <= 11 *
## | | | | [16] V2 > 11 *
## | | | [17] V9 > 14 *
##
## $nodes[[146]]
## [1] root
## | [2] V5 <= 1
## | | [3] V7 <= 90
## | | | [4] V5 <= 0
## | | | | [5] V8 <= 775 *
## | | | | [6] V8 > 775 *
## | | | [7] V5 > 0
## | | | | [8] V4 <= 1
## | | | | | [9] V7 <= 80 *
## | | | | | [10] V7 > 80 *
## | | | | [11] V4 > 1 *
## | | [12] V7 > 90 *
## | [13] V5 > 1
## | | [14] V6 <= 60 *
## | | [15] V6 > 60 *
##
## $nodes[[147]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V5 <= 0
## | | | [5] V3 <= 64 *
## | | | [6] V3 > 64 *
## | | [7] V5 > 0
## | | | [8] V5 <= 1
## | | | | [9] V6 <= 80
## | | | | | [10] V2 <= 13
## | | | | | | [11] V7 <= 70 *
## | | | | | | [12] V7 > 70 *
## | | | | | [13] V2 > 13 *
## | | | | [14] V6 > 80 *
## | | | [15] V5 > 1 *
##
## $nodes[[148]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V6 <= 80 *
## | | | [5] V6 > 80
## | | | | [6] V8 <= 1175
## | | | | | [7] V2 <= 11 *
## | | | | | [8] V2 > 11 *
## | | | | [9] V8 > 1175 *
## | | [10] V4 > 1
## | | | [11] V3 <= 63
## | | | | [12] V2 <= 10 *
## | | | | [13] V2 > 10 *
## | | | [14] V3 > 63 *
## | [15] V5 > 1
## | | [16] V6 <= 60 *
## | | [17] V6 > 60 *
##
## $nodes[[149]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V2 <= 4 *
## | | | [5] V2 > 4
## | | | | [6] V9 <= 15
## | | | | | [7] V7 <= 90
## | | | | | | [8] V8 <= 993 *
## | | | | | | [9] V8 > 993 *
## | | | | | [10] V7 > 90 *
## | | | | [11] V9 > 15 *
## | | [12] V5 > 1 *
## | [13] V4 > 1
## | | [14] V5 <= 0 *
## | | [15] V5 > 0
## | | | [16] V5 <= 1 *
## | | | [17] V5 > 1 *
##
## $nodes[[150]]
## [1] root
## | [2] V6 <= 70
## | | [3] V7 <= 60 *
## | | [4] V7 > 60 *
## | [5] V6 > 70
## | | [6] V5 <= 0
## | | | [7] V7 <= 80 *
## | | | [8] V7 > 80 *
## | | [9] V5 > 0
## | | | [10] V9 <= 14
## | | | | [11] V7 <= 80
## | | | | | [12] V2 <= 13 *
## | | | | | [13] V2 > 13 *
## | | | | [14] V7 > 80 *
## | | | [15] V9 > 14 *
##
## $nodes[[151]]
## [1] root
## | [2] V6 <= 70
## | | [3] V2 <= 12 *
## | | [4] V2 > 12 *
## | [5] V6 > 70
## | | [6] V4 <= 1
## | | | [7] V3 <= 47 *
## | | | [8] V3 > 47
## | | | | [9] V8 <= 1125
## | | | | | [10] V3 <= 60 *
## | | | | | [11] V3 > 60
## | | | | | | [12] V7 <= 80 *
## | | | | | | [13] V7 > 80 *
## | | | | [14] V8 > 1125 *
## | | [15] V4 > 1
## | | | [16] V9 <= 0 *
## | | | [17] V9 > 0 *
##
## $nodes[[152]]
## [1] root
## | [2] V6 <= 70
## | | [3] V7 <= 70
## | | | [4] V9 <= 3 *
## | | | [5] V9 > 3 *
## | | [6] V7 > 70 *
## | [7] V6 > 70
## | | [8] V4 <= 1
## | | | [9] V5 <= 0 *
## | | | [10] V5 > 0
## | | | | [11] V6 <= 80 *
## | | | | [12] V6 > 80 *
## | | [13] V4 > 1
## | | | [14] V6 <= 90
## | | | | [15] V7 <= 80 *
## | | | | [16] V7 > 80 *
## | | | [17] V6 > 90 *
##
## $nodes[[153]]
## [1] root
## | [2] V3 <= 65
## | | [3] V7 <= 90
## | | | [4] V9 <= 3 *
## | | | [5] V9 > 3
## | | | | [6] V6 <= 70 *
## | | | | [7] V6 > 70
## | | | | | [8] V2 <= 4 *
## | | | | | [9] V2 > 4 *
## | | [10] V7 > 90 *
## | [11] V3 > 65
## | | [12] V3 <= 71
## | | | [13] V8 <= 875 *
## | | | [14] V8 > 875
## | | | | [15] V2 <= 12 *
## | | | | [16] V2 > 12 *
## | | [17] V3 > 71 *
##
## $nodes[[154]]
## [1] root
## | [2] V3 <= 44 *
## | [3] V3 > 44
## | | [4] V5 <= 1
## | | | [5] V9 <= 23
## | | | | [6] V4 <= 1
## | | | | | [7] V6 <= 90
## | | | | | | [8] V2 <= 7 *
## | | | | | | [9] V2 > 7 *
## | | | | | [10] V6 > 90 *
## | | | | [11] V4 > 1
## | | | | | [12] V2 <= 12 *
## | | | | | [13] V2 > 12 *
## | | | [14] V9 > 23 *
## | | [15] V5 > 1
## | | | [16] V6 <= 60 *
## | | | [17] V6 > 60 *
##
## $nodes[[155]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V4 <= 1
## | | | [5] V3 <= 70
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V2 <= 13
## | | | | | | [9] V2 <= 11 *
## | | | | | | [10] V2 > 11 *
## | | | | | [11] V2 > 13 *
## | | | [12] V3 > 70 *
## | | [13] V4 > 1
## | | | [14] V7 <= 90
## | | | | [15] V2 <= 12 *
## | | | | [16] V2 > 12 *
## | | | [17] V7 > 90 *
##
## $nodes[[156]]
## [1] root
## | [2] V7 <= 90
## | | [3] V3 <= 63
## | | | [4] V7 <= 60 *
## | | | [5] V7 > 60
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0
## | | | | | [8] V4 <= 1 *
## | | | | | [9] V4 > 1 *
## | | [10] V3 > 63
## | | | [11] V8 <= 1125
## | | | | [12] V2 <= 15
## | | | | | [13] V3 <= 71
## | | | | | | [14] V3 <= 68 *
## | | | | | | [15] V3 > 68 *
## | | | | | [16] V3 > 71 *
## | | | | [17] V2 > 15 *
## | | | [18] V8 > 1125 *
## | [19] V7 > 90 *
##
## $nodes[[157]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 60
## | | | [4] V5 <= 0 *
## | | | [5] V5 > 0 *
## | | [6] V3 > 60
## | | | [7] V9 <= 14
## | | | | [8] V4 <= 1
## | | | | | [9] V9 <= 2 *
## | | | | | [10] V9 > 2 *
## | | | | [11] V4 > 1 *
## | | | [12] V9 > 14 *
## | [13] V5 > 1
## | | [14] V6 <= 60 *
## | | [15] V6 > 60 *
##
## $nodes[[158]]
## [1] root
## | [2] V6 <= 70
## | | [3] V9 <= 16 *
## | | [4] V9 > 16 *
## | [5] V6 > 70
## | | [6] V7 <= 60 *
## | | [7] V7 > 60
## | | | [8] V4 <= 1
## | | | | [9] V3 <= 60 *
## | | | | [10] V3 > 60
## | | | | | [11] V3 <= 68 *
## | | | | | [12] V3 > 68 *
## | | | [13] V4 > 1
## | | | | [14] V5 <= 0 *
## | | | | [15] V5 > 0 *
##
## $nodes[[159]]
## [1] root
## | [2] V3 <= 45 *
## | [3] V3 > 45
## | | [4] V4 <= 1
## | | | [5] V9 <= 27
## | | | | [6] V6 <= 70 *
## | | | | [7] V6 > 70
## | | | | | [8] V7 <= 90
## | | | | | | [9] V8 <= 1100
## | | | | | | | [10] V2 <= 11 *
## | | | | | | | [11] V2 > 11 *
## | | | | | | [12] V8 > 1100 *
## | | | | | [13] V7 > 90 *
## | | | [14] V9 > 27 *
## | | [15] V4 > 1
## | | | [16] V7 <= 80
## | | | | [17] V5 <= 1 *
## | | | | [18] V5 > 1 *
## | | | [19] V7 > 80 *
##
## $nodes[[160]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 70
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70
## | | | | [6] V9 <= 6 *
## | | | | [7] V9 > 6
## | | | | | [8] V8 <= 875 *
## | | | | | [9] V8 > 875 *
## | | [10] V3 > 70 *
## | [11] V4 > 1
## | | [12] V9 <= 0 *
## | | [13] V9 > 0
## | | | [14] V8 <= 825 *
## | | | [15] V8 > 825 *
##
## $nodes[[161]]
## [1] root
## | [2] V2 <= 15
## | | [3] V5 <= 1
## | | | [4] V5 <= 0
## | | | | [5] V9 <= 5 *
## | | | | [6] V9 > 5 *
## | | | [7] V5 > 0
## | | | | [8] V4 <= 1
## | | | | | [9] V6 <= 80 *
## | | | | | [10] V6 > 80 *
## | | | | [11] V4 > 1 *
## | | [12] V5 > 1 *
## | [13] V2 > 15
## | | [14] V2 <= 16 *
## | | [15] V2 > 16 *
##
## $nodes[[162]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V9 <= 6
## | | | | [5] V2 <= 12 *
## | | | | [6] V2 > 12 *
## | | | [7] V9 > 6 *
## | | [8] V5 > 0
## | | | [9] V8 <= 925
## | | | | [10] V9 <= 14 *
## | | | | [11] V9 > 14 *
## | | | [12] V8 > 925
## | | | | [13] V8 <= 1060 *
## | | | | [14] V8 > 1060 *
## | [15] V5 > 1
## | | [16] V2 <= 7 *
## | | [17] V2 > 7 *
##
## $nodes[[163]]
## [1] root
## | [2] V3 <= 45 *
## | [3] V3 > 45
## | | [4] V5 <= 0
## | | | [5] V3 <= 64 *
## | | | [6] V3 > 64 *
## | | [7] V5 > 0
## | | | [8] V9 <= 27
## | | | | [9] V6 <= 70
## | | | | | [10] V8 <= 1025 *
## | | | | | [11] V8 > 1025 *
## | | | | [12] V6 > 70
## | | | | | [13] V4 <= 1
## | | | | | | [14] V6 <= 80 *
## | | | | | | [15] V6 > 80 *
## | | | | | [16] V4 > 1 *
## | | | [17] V9 > 27 *
##
## $nodes[[164]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V9 <= 12
## | | | | | [7] V3 <= 60 *
## | | | | | [8] V3 > 60 *
## | | | | [9] V9 > 12 *
## | | [10] V4 > 1
## | | | [11] V5 <= 0 *
## | | | [12] V5 > 0 *
## | [13] V5 > 1
## | | [14] V9 <= 10 *
## | | [15] V9 > 10 *
##
## $nodes[[165]]
## [1] root
## | [2] V4 <= 1
## | | [3] V8 <= 1275
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70
## | | | | [6] V2 <= 11
## | | | | | [7] V2 <= 6 *
## | | | | | [8] V2 > 6 *
## | | | | [9] V2 > 11 *
## | | [10] V8 > 1275 *
## | [11] V4 > 1
## | | [12] V5 <= 0 *
## | | [13] V5 > 0
## | | | [14] V2 <= 13 *
## | | | [15] V2 > 13 *
##
## $nodes[[166]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V5 <= 0
## | | | | [5] V8 <= 1025 *
## | | | | [6] V8 > 1025 *
## | | | [7] V5 > 0
## | | | | [8] V8 <= 875 *
## | | | | [9] V8 > 875 *
## | | [10] V3 > 64
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V2 <= 13 *
## | | [15] V2 > 13 *
##
## $nodes[[167]]
## [1] root
## | [2] V7 <= 70
## | | [3] V6 <= 80
## | | | [4] V5 <= 1 *
## | | | [5] V5 > 1
## | | | | [6] V9 <= 20 *
## | | | | [7] V9 > 20 *
## | | [8] V6 > 80 *
## | [9] V7 > 70
## | | [10] V5 <= 0
## | | | [11] V2 <= 13 *
## | | | [12] V2 > 13 *
## | | [13] V5 > 0
## | | | [14] V3 <= 53 *
## | | | [15] V3 > 53
## | | | | [16] V6 <= 80 *
## | | | | [17] V6 > 80 *
##
## $nodes[[168]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 71
## | | | [4] V5 <= 1
## | | | | [5] V8 <= 1150
## | | | | | [6] V3 <= 64 *
## | | | | | [7] V3 > 64 *
## | | | | [8] V8 > 1150 *
## | | | [9] V5 > 1 *
## | | [10] V3 > 71 *
## | [11] V4 > 1
## | | [12] V2 <= 10 *
## | | [13] V2 > 10
## | | | [14] V9 <= 3 *
## | | | [15] V9 > 3 *
##
## $nodes[[169]]
## [1] root
## | [2] V3 <= 46 *
## | [3] V3 > 46
## | | [4] V4 <= 1
## | | | [5] V5 <= 1
## | | | | [6] V7 <= 90
## | | | | | [7] V8 <= 1125
## | | | | | | [8] V2 <= 11 *
## | | | | | | [9] V2 > 11 *
## | | | | | [10] V8 > 1125 *
## | | | | [11] V7 > 90 *
## | | | [12] V5 > 1 *
## | | [13] V4 > 1
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0
## | | | | [16] V2 <= 16 *
## | | | | [17] V2 > 16 *
##
## $nodes[[170]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 48 *
## | | [4] V3 > 48
## | | | [5] V5 <= 1
## | | | | [6] V7 <= 90
## | | | | | [7] V7 <= 70 *
## | | | | | [8] V7 > 70 *
## | | | | [9] V7 > 90 *
## | | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V5 <= 1
## | | | [13] V7 <= 80 *
## | | | [14] V7 > 80 *
## | | [15] V5 > 1 *
##
## $nodes[[171]]
## [1] root
## | [2] V3 <= 66
## | | [3] V4 <= 1
## | | | [4] V7 <= 70 *
## | | | [5] V7 > 70
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80 *
## | | [8] V4 > 1
## | | | [9] V2 <= 16
## | | | | [10] V5 <= 0 *
## | | | | [11] V5 > 0 *
## | | | [12] V2 > 16 *
## | [13] V3 > 66
## | | [14] V4 <= 1
## | | | [15] V5 <= 1 *
## | | | [16] V5 > 1 *
## | | [17] V4 > 1 *
##
## $nodes[[172]]
## [1] root
## | [2] V7 <= 70
## | | [3] V9 <= 20
## | | | [4] V4 <= 1 *
## | | | [5] V4 > 1 *
## | | [6] V9 > 20 *
## | [7] V7 > 70
## | | [8] V3 <= 63
## | | | [9] V4 <= 1
## | | | | [10] V6 <= 80 *
## | | | | [11] V6 > 80 *
## | | | [12] V4 > 1 *
## | | [13] V3 > 63
## | | | [14] V6 <= 80 *
## | | | [15] V6 > 80 *
##
## $nodes[[173]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 80
## | | | [4] V5 <= 1 *
## | | | [5] V5 > 1 *
## | | [6] V6 > 80
## | | | [7] V9 <= -1 *
## | | | [8] V9 > -1
## | | | | [9] V9 <= 4 *
## | | | | [10] V9 > 4 *
## | [11] V4 > 1
## | | [12] V2 <= 11
## | | | [13] V6 <= 80 *
## | | | [14] V6 > 80 *
## | | [15] V2 > 11 *
##
## $nodes[[174]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V9 <= 17
## | | | | [5] V9 <= 8
## | | | | | [6] V5 <= 0 *
## | | | | | [7] V5 > 0 *
## | | | | [8] V9 > 8 *
## | | | [9] V9 > 17 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V7 <= 60 *
## | | [13] V7 > 60
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0
## | | | | [16] V8 <= 825 *
## | | | | [17] V8 > 825 *
##
## $nodes[[175]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 80
## | | | [4] V9 <= 20
## | | | | [5] V5 <= 1 *
## | | | | [6] V5 > 1 *
## | | | [7] V9 > 20 *
## | | [8] V6 > 80
## | | | [9] V9 <= 6 *
## | | | [10] V9 > 6 *
## | [11] V4 > 1
## | | [12] V9 <= -1 *
## | | [13] V9 > -1
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0
## | | | | [16] V6 <= 70 *
## | | | | [17] V6 > 70 *
##
## $nodes[[176]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 64
## | | | [4] V2 <= 12
## | | | | [5] V3 <= 50 *
## | | | | [6] V3 > 50
## | | | | | [7] V5 <= 0 *
## | | | | | [8] V5 > 0 *
## | | | [9] V2 > 12 *
## | | [10] V3 > 64
## | | | [11] V9 <= 10
## | | | | [12] V5 <= 0 *
## | | | | [13] V5 > 0 *
## | | | [14] V9 > 10 *
## | [15] V5 > 1
## | | [16] V6 <= 60 *
## | | [17] V6 > 60 *
##
## $nodes[[177]]
## [1] root
## | [2] V4 <= 1
## | | [3] V2 <= 15
## | | | [4] V5 <= 1
## | | | | [5] V8 <= 1175
## | | | | | [6] V6 <= 80 *
## | | | | | [7] V6 > 80 *
## | | | | [8] V8 > 1175 *
## | | | [9] V5 > 1 *
## | | [10] V2 > 15 *
## | [11] V4 > 1
## | | [12] V6 <= 70 *
## | | [13] V6 > 70
## | | | [14] V8 <= 975 *
## | | | [15] V8 > 975 *
##
## $nodes[[178]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V3 <= 63
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0 *
## | | | [7] V3 > 63
## | | | | [8] V9 <= 17
## | | | | | [9] V6 <= 80 *
## | | | | | [10] V6 > 80 *
## | | | | [11] V9 > 17 *
## | | [12] V4 > 1
## | | | [13] V5 <= 0 *
## | | | [14] V5 > 0 *
## | [15] V5 > 1
## | | [16] V3 <= 62 *
## | | [17] V3 > 62 *
##
## $nodes[[179]]
## [1] root
## | [2] V5 <= 1
## | | [3] V3 <= 51 *
## | | [4] V3 > 51
## | | | [5] V5 <= 0
## | | | | [6] V9 <= 5 *
## | | | | [7] V9 > 5 *
## | | | [8] V5 > 0
## | | | | [9] V6 <= 80
## | | | | | [10] V9 <= 14 *
## | | | | | [11] V9 > 14 *
## | | | | [12] V6 > 80
## | | | | | [13] V8 <= 875 *
## | | | | | [14] V8 > 875 *
## | [15] V5 > 1
## | | [16] V8 <= 413 *
## | | [17] V8 > 413 *
##
## $nodes[[180]]
## [1] root
## | [2] V7 <= 60 *
## | [3] V7 > 60
## | | [4] V4 <= 1
## | | | [5] V7 <= 90
## | | | | [6] V8 <= 910 *
## | | | | [7] V8 > 910
## | | | | | [8] V9 <= -1 *
## | | | | | [9] V9 > -1
## | | | | | | [10] V2 <= 11 *
## | | | | | | [11] V2 > 11 *
## | | | [12] V7 > 90 *
## | | [13] V4 > 1
## | | | [14] V7 <= 80 *
## | | | [15] V7 > 80
## | | | | [16] V9 <= 6 *
## | | | | [17] V9 > 6 *
##
## $nodes[[181]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V6 <= 70 *
## | | | [6] V6 > 70
## | | | | [7] V3 <= 63
## | | | | | [8] V3 <= 58 *
## | | | | | [9] V3 > 58 *
## | | | | [10] V3 > 63 *
## | [11] V4 > 1
## | | [12] V7 <= 80
## | | | [13] V3 <= 60 *
## | | | [14] V3 > 60 *
## | | [15] V7 > 80 *
##
## $nodes[[182]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V8 <= 925 *
## | | | [5] V8 > 925
## | | | | [6] V5 <= 0 *
## | | | | [7] V5 > 0 *
## | | [8] V4 > 1
## | | | [9] V8 <= 925 *
## | | | [10] V8 > 925 *
## | [11] V5 > 1
## | | [12] V9 <= 11 *
## | | [13] V9 > 11 *
##
## $nodes[[183]]
## [1] root
## | [2] V5 <= 0
## | | [3] V8 <= 588 *
## | | [4] V8 > 588
## | | | [5] V7 <= 80 *
## | | | [6] V7 > 80 *
## | [7] V5 > 0
## | | [8] V2 <= 12
## | | | [9] V6 <= 70 *
## | | | [10] V6 > 70
## | | | | [11] V3 <= 64 *
## | | | | [12] V3 > 64 *
## | | [13] V2 > 12
## | | | [14] V9 <= 15
## | | | | [15] V4 <= 1 *
## | | | | [16] V4 > 1 *
## | | | [17] V9 > 15 *
##
## $nodes[[184]]
## [1] root
## | [2] V3 <= 65
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V8 <= 1060
## | | | | [6] V6 <= 80 *
## | | | | [7] V6 > 80
## | | | | | [8] V7 <= 80 *
## | | | | | [9] V7 > 80 *
## | | | [10] V8 > 1060 *
## | [11] V3 > 65
## | | [12] V4 <= 1
## | | | [13] V5 <= 1 *
## | | | [14] V5 > 1 *
## | | [15] V4 > 1 *
##
## $nodes[[185]]
## [1] root
## | [2] V6 <= 70
## | | [3] V4 <= 1 *
## | | [4] V4 > 1 *
## | [5] V6 > 70
## | | [6] V4 <= 1
## | | | [7] V9 <= 2 *
## | | | [8] V9 > 2
## | | | | [9] V5 <= 0 *
## | | | | [10] V5 > 0
## | | | | | [11] V7 <= 70 *
## | | | | | [12] V7 > 70 *
## | | [13] V4 > 1
## | | | [14] V3 <= 59 *
## | | | [15] V3 > 59 *
##
## $nodes[[186]]
## [1] root
## | [2] V5 <= 1
## | | [3] V8 <= 575 *
## | | [4] V8 > 575
## | | | [5] V8 <= 1025
## | | | | [6] V9 <= 7
## | | | | | [7] V4 <= 1 *
## | | | | | [8] V4 > 1 *
## | | | | [9] V9 > 7 *
## | | | [10] V8 > 1025
## | | | | [11] V4 <= 1
## | | | | | [12] V9 <= 2 *
## | | | | | [13] V9 > 2 *
## | | | | [14] V4 > 1 *
## | [15] V5 > 1
## | | [16] V2 <= 13 *
## | | [17] V2 > 13 *
##
## $nodes[[187]]
## [1] root
## | [2] V4 <= 1
## | | [3] V3 <= 71
## | | | [4] V9 <= 15
## | | | | [5] V9 <= -1 *
## | | | | [6] V9 > -1
## | | | | | [7] V2 <= 5 *
## | | | | | [8] V2 > 5
## | | | | | | [9] V9 <= 8 *
## | | | | | | [10] V9 > 8 *
## | | | [11] V9 > 15 *
## | | [12] V3 > 71 *
## | [13] V4 > 1
## | | [14] V9 <= 13
## | | | [15] V5 <= 0 *
## | | | [16] V5 > 0 *
## | | [17] V9 > 13 *
##
## $nodes[[188]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 0 *
## | | [4] V5 > 0
## | | | [5] V9 <= 24
## | | | | [6] V5 <= 1
## | | | | | [7] V7 <= 70 *
## | | | | | [8] V7 > 70 *
## | | | | [9] V5 > 1 *
## | | | [10] V9 > 24 *
## | [11] V4 > 1
## | | [12] V5 <= 0 *
## | | [13] V5 > 0
## | | | [14] V2 <= 12 *
## | | | [15] V2 > 12 *
##
## $nodes[[189]]
## [1] root
## | [2] V4 <= 1
## | | [3] V7 <= 60 *
## | | [4] V7 > 60
## | | | [5] V5 <= 0 *
## | | | [6] V5 > 0
## | | | | [7] V3 <= 70
## | | | | | [8] V8 <= 993 *
## | | | | | [9] V8 > 993 *
## | | | | [10] V3 > 70 *
## | [11] V4 > 1
## | | [12] V7 <= 90
## | | | [13] V7 <= 80 *
## | | | [14] V7 > 80 *
## | | [15] V7 > 90 *
##
## $nodes[[190]]
## [1] root
## | [2] V3 <= 70
## | | [3] V7 <= 90
## | | | [4] V4 <= 1
## | | | | [5] V5 <= 0 *
## | | | | [6] V5 > 0
## | | | | | [7] V8 <= 1025 *
## | | | | | [8] V8 > 1025 *
## | | | [9] V4 > 1
## | | | | [10] V5 <= 0 *
## | | | | [11] V5 > 0 *
## | | [12] V7 > 90 *
## | [13] V3 > 70
## | | [14] V5 <= 1 *
## | | [15] V5 > 1 *
##
## $nodes[[191]]
## [1] root
## | [2] V3 <= 71
## | | [3] V2 <= 21
## | | | [4] V6 <= 70 *
## | | | [5] V6 > 70
## | | | | [6] V3 <= 64
## | | | | | [7] V5 <= 0 *
## | | | | | [8] V5 > 0
## | | | | | | [9] V7 <= 80 *
## | | | | | | [10] V7 > 80 *
## | | | | [11] V3 > 64 *
## | | [12] V2 > 21 *
## | [13] V3 > 71 *
##
## $nodes[[192]]
## [1] root
## | [2] V6 <= 70
## | | [3] V2 <= 7 *
## | | [4] V2 > 7 *
## | [5] V6 > 70
## | | [6] V9 <= 5
## | | | [7] V7 <= 90
## | | | | [8] V6 <= 80 *
## | | | | [9] V6 > 80 *
## | | | [10] V7 > 90 *
## | | [11] V9 > 5
## | | | [12] V3 <= 64
## | | | | [13] V3 <= 56 *
## | | | | [14] V3 > 56 *
## | | | [15] V3 > 64 *
##
## $nodes[[193]]
## [1] root
## | [2] V5 <= 0
## | | [3] V9 <= 3 *
## | | [4] V9 > 3
## | | | [5] V2 <= 4 *
## | | | [6] V2 > 4 *
## | [7] V5 > 0
## | | [8] V7 <= 60 *
## | | [9] V7 > 60
## | | | [10] V2 <= 5 *
## | | | [11] V2 > 5
## | | | | [12] V9 <= 7 *
## | | | | [13] V9 > 7 *
##
## $nodes[[194]]
## [1] root
## | [2] V5 <= 1
## | | [3] V5 <= 0
## | | | [4] V7 <= 80 *
## | | | [5] V7 > 80 *
## | | [6] V5 > 0
## | | | [7] V4 <= 1
## | | | | [8] V6 <= 80
## | | | | | [9] V9 <= 15 *
## | | | | | [10] V9 > 15 *
## | | | | [11] V6 > 80 *
## | | | [12] V4 > 1
## | | | | [13] V7 <= 80 *
## | | | | [14] V7 > 80 *
## | [15] V5 > 1
## | | [16] V2 <= 13 *
## | | [17] V2 > 13 *
##
## $nodes[[195]]
## [1] root
## | [2] V4 <= 1
## | | [3] V9 <= 27
## | | | [4] V5 <= 1
## | | | | [5] V2 <= 11
## | | | | | [6] V7 <= 70 *
## | | | | | [7] V7 > 70 *
## | | | | [8] V2 > 11 *
## | | | [9] V5 > 1 *
## | | [10] V9 > 27 *
## | [11] V4 > 1
## | | [12] V2 <= 12
## | | | [13] V6 <= 80 *
## | | | [14] V6 > 80 *
## | | [15] V2 > 12 *
##
## $nodes[[196]]
## [1] root
## | [2] V4 <= 1
## | | [3] V6 <= 70 *
## | | [4] V6 > 70
## | | | [5] V5 <= 0 *
## | | | [6] V5 > 0
## | | | | [7] V3 <= 59 *
## | | | | [8] V3 > 59
## | | | | | [9] V9 <= 8 *
## | | | | | [10] V9 > 8 *
## | [11] V4 > 1
## | | [12] V7 <= 80
## | | | [13] V9 <= 0 *
## | | | [14] V9 > 0 *
## | | [15] V7 > 80 *
##
## $nodes[[197]]
## [1] root
## | [2] V7 <= 60
## | | [3] V5 <= 1 *
## | | [4] V5 > 1 *
## | [5] V7 > 60
## | | [6] V4 <= 1
## | | | [7] V8 <= 488 *
## | | | [8] V8 > 488
## | | | | [9] V2 <= 15
## | | | | | [10] V5 <= 0 *
## | | | | | [11] V5 > 0 *
## | | | | [12] V2 > 15 *
## | | [13] V4 > 1
## | | | [14] V5 <= 0 *
## | | | [15] V5 > 0
## | | | | [16] V3 <= 65 *
## | | | | [17] V3 > 65 *
##
## $nodes[[198]]
## [1] root
## | [2] V5 <= 1
## | | [3] V4 <= 1
## | | | [4] V6 <= 80
## | | | | [5] V9 <= 14 *
## | | | | [6] V9 > 14 *
## | | | [7] V6 > 80
## | | | | [8] V9 <= 6 *
## | | | | [9] V9 > 6 *
## | | [10] V4 > 1
## | | | [11] V6 <= 80 *
## | | | [12] V6 > 80 *
## | [13] V5 > 1
## | | [14] V9 <= 10 *
## | | [15] V9 > 10 *
##
## $nodes[[199]]
## [1] root
## | [2] V4 <= 1
## | | [3] V5 <= 1
## | | | [4] V3 <= 65
## | | | | [5] V9 <= 1 *
## | | | | [6] V9 > 1
## | | | | | [7] V3 <= 56 *
## | | | | | [8] V3 > 56 *
## | | | [9] V3 > 65 *
## | | [10] V5 > 1 *
## | [11] V4 > 1
## | | [12] V7 <= 90
## | | | [13] V5 <= 0 *
## | | | [14] V5 > 0
## | | | | [15] V9 <= 0 *
## | | | | [16] V9 > 0 *
## | | [17] V7 > 90 *
##
## $nodes[[200]]
## [1] root
## | [2] V7 <= 70
## | | [3] V6 <= 70
## | | | [4] V9 <= 11 *
## | | | [5] V9 > 11 *
## | | [6] V6 > 70 *
## | [7] V7 > 70
## | | [8] V4 <= 1
## | | | [9] V2 <= 6 *
## | | | [10] V2 > 6 *
## | | [11] V4 > 1
## | | | [12] V3 <= 57 *
## | | | [13] V3 > 57 *
##
##
## $data
## Surv(time, status) inst age sex ph.ecog ph.karno pat.karno meal.cal
## 9 218 1 53 1 1 70 80 825
## 10 166 7 61 1 2 70 70 271
## 11 170 6 57 1 1 80 80 1025
## 15 567 12 57 1 1 80 70 2600
## 17 613 22 70 1 1 90 100 1150
## 18 707 16 63 1 2 50 70 1025
## 19 61 1 56 2 2 60 60 238
## 21 301 11 67 1 1 80 80 1025
## 22 81 6 49 2 0 100 70 1175
## 24 371 15 58 1 0 90 100 975
## 26 520 12 70 2 1 90 80 825
## 27 574 4 60 1 0 100 100 1025
## 28 118 13 70 1 3 60 70 1075
## 29 390 13 53 1 1 80 70 875
## 30 12 1 74 1 2 70 50 305
## 31 473 12 69 2 1 90 90 1025
## 32 26 1 73 1 2 60 70 388
## 34 107 16 60 2 2 50 60 925
## 35 53 12 61 1 2 70 100 1075
## 37 814 22 65 1 2 70 60 513
## 38 965+ 15 66 2 1 70 90 875
## 39 93 1 74 1 2 50 40 1225
## 40 731 1 64 2 1 80 100 1175
## 41 460 5 70 1 1 80 60 975
## 42 153 11 73 2 2 60 70 1075
## 43 433 10 59 2 0 90 90 363
## 45 583 7 68 1 1 60 70 1025
## 46 95 7 76 2 2 60 60 625
## 47 303 1 74 1 0 90 70 463
## 48 519 3 63 1 1 80 70 1025
## 49 643 13 74 1 0 90 90 1425
## 50 765 22 50 2 1 90 100 1175
## 53 53 21 68 1 0 90 100 1025
## 54 246 1 58 1 0 100 90 1175
## 55 689 6 59 1 1 90 80 1300
## 57 5 5 65 2 0 100 80 338
## 59 687 3 58 2 1 80 80 1225
## 60 345 1 64 2 1 90 80 1075
## 61 444 22 75 2 2 70 70 438
## 62 223 12 48 1 1 90 80 1300
## 64 60 11 65 2 1 90 80 1025
## 65 163 3 69 1 1 80 60 1125
## 66 65 3 68 1 2 70 50 825
## 68 821+ 5 64 2 0 90 70 1025
## 69 428 22 68 1 0 100 80 1039
## 70 230 6 67 1 1 80 100 488
## 71 840+ 13 63 1 0 90 90 1175
## 72 305 3 48 2 1 80 90 538
## 73 11 5 74 1 2 70 100 1175
## 75 226 21 53 2 1 90 80 825
## 76 426 12 71 2 1 90 90 1075
## 77 705 1 51 2 0 100 80 1300
## 78 363 6 56 2 1 80 70 1225
## 80 176 1 73 1 0 90 70 169
## 81 791 4 59 1 0 100 80 768
## 82 95 13 55 1 1 70 90 1500
## 83 196+ 11 42 1 1 80 80 1425
## 84 167 21 44 2 1 80 90 588
## 85 806+ 16 44 1 1 80 80 1025
## 86 284 6 71 1 1 80 90 1100
## 87 641 22 62 2 1 80 80 1150
## 88 147 21 61 1 0 100 90 1175
## 89 740+ 13 44 2 1 90 80 588
## 90 163 1 72 1 2 70 70 910
## 91 655 11 63 1 0 100 90 975
## 93 88 5 66 1 1 90 80 875
## 94 245 10 57 2 1 80 60 280
## 96 30 12 72 1 2 80 60 288
## 99 477 11 64 1 1 90 100 910
## 101 559+ 1 58 2 0 100 100 710
## 102 450 6 69 2 1 80 90 1175
## 106 156 12 66 1 1 80 90 875
## 107 529+ 26 54 2 1 80 100 975
## 109 429 21 55 1 1 100 80 975
## 110 351 3 75 2 2 60 50 925
## 111 15 13 69 1 0 90 70 575
## 112 181 1 44 1 1 80 90 1175
## 113 283 10 80 1 1 80 100 1030
## 116 13 1 76 1 2 70 70 413
## 117 212 3 49 1 2 70 60 675
## 118 524 1 68 1 2 60 70 1300
## 119 288 16 66 1 2 70 60 613
## 120 363 15 80 1 1 80 90 346
## 122 199 26 60 2 2 70 80 675
## 123 550 3 69 2 1 70 80 910
## 124 54 11 72 1 2 60 60 768
## 125 558 1 70 1 0 90 90 1025
## 126 207 22 66 1 1 80 80 925
## 127 92 7 50 1 1 80 60 1075
## 128 60 12 64 1 1 80 90 993
## 129 551+ 16 77 2 2 80 60 750
## 131 293 4 59 2 1 80 80 925
## 133 353 6 47 1 0 100 90 1225
## 135 267 1 67 1 0 90 70 313
## 136 511+ 22 74 2 2 60 40 96
## 139 457 1 54 1 1 90 90 975
## 140 337 5 56 1 0 100 100 1500
## 141 201 21 73 2 2 70 60 1225
## 142 404+ 3 74 1 1 80 70 413
## 143 222 26 76 1 2 70 70 1500
## 144 62 1 65 2 1 80 90 1075
## 145 458+ 11 57 1 1 80 100 513
## 147 353 16 71 1 0 100 80 775
## 148 163 16 54 1 1 90 80 1225
## 149 31 12 82 1 0 100 90 413
## 151 229 13 70 1 1 70 60 1175
## 155 156 32 55 1 2 70 30 1025
## 158 291 4 62 1 2 70 60 475
## 159 179 12 63 1 1 80 70 538
## 160 376+ 1 56 2 1 80 90 825
## 161 384+ 32 62 2 0 90 90 588
## 162 268 10 44 2 1 90 100 2450
## 163 292+ 11 69 1 2 60 70 2450
## 164 142 6 63 1 1 90 80 875
## 165 413+ 7 64 1 1 80 70 413
## 166 266+ 16 57 2 0 90 90 1075
## 168 320 21 46 1 0 100 100 860
## 169 181 6 61 1 1 90 90 730
## 170 285 12 65 1 0 100 90 1025
## 171 301+ 13 61 1 1 90 100 825
## 172 348 2 58 2 0 90 80 1225
## 173 197 2 56 1 1 90 60 768
## 174 382+ 16 43 2 0 100 90 338
## 175 303+ 1 53 1 1 90 80 1225
## 176 296+ 13 59 2 1 80 100 1025
## 177 180 1 56 1 2 60 80 1225
## 179 145 1 53 2 1 80 90 588
## 180 269+ 7 74 2 0 100 100 588
## 181 300+ 13 60 1 0 100 100 975
## 182 284+ 1 39 1 0 100 90 1225
## 185 292+ 12 51 2 0 90 80 1225
## 186 332+ 12 45 2 0 90 100 975
## 187 285 2 72 2 2 70 90 463
## 188 259+ 3 58 1 0 90 80 1300
## 189 110 15 64 1 1 80 60 1025
## 190 286 22 53 1 0 90 90 1225
## 191 270 16 72 1 1 80 90 488
## 194 225+ 1 64 1 1 90 80 825
## 195 269 22 71 1 1 90 90 1300
## 196 225+ 12 70 1 0 100 100 1175
## 197 243+ 32 63 2 1 80 90 825
## 199 276+ 1 52 2 0 100 80 975
## 200 135 32 60 1 1 90 70 1275
## 201 79 15 64 2 1 90 90 488
## 202 59 22 73 1 1 60 60 2200
## 203 240+ 32 63 2 0 90 100 1025
## 204 202+ 3 50 2 0 100 100 635
## 205 235+ 26 63 2 0 100 90 413
## 208 239 13 50 2 2 60 60 1025
## 211 252+ 1 60 2 0 100 90 488
## 212 221+ 6 67 1 1 80 70 413
## 213 185+ 15 69 1 1 90 70 1075
## 216 222+ 11 65 1 1 90 70 1025
## 218 183 21 76 1 2 80 60 825
## 219 211+ 11 70 2 2 70 30 131
## 220 175+ 2 57 2 0 80 80 725
## 221 197+ 22 67 1 1 80 90 1500
## 222 203+ 11 71 2 1 80 90 1025
## 225 191+ 13 39 1 0 90 90 2350
## 226 105+ 32 75 2 2 60 70 1025
## 227 174+ 6 66 1 1 90 100 1075
## 228 177+ 22 58 2 1 80 90 1060
## wt.loss
## 9 16
## 10 34
## 11 27
## 15 60
## 17 -5
## 18 22
## 19 10
## 21 17
## 22 -8
## 24 13
## 26 6
## 27 -13
## 28 20
## 29 -7
## 30 20
## 31 -1
## 32 20
## 34 -15
## 35 10
## 37 28
## 38 4
## 39 24
## 40 15
## 41 10
## 42 11
## 43 27
## 45 7
## 46 -24
## 47 30
## 48 10
## 49 2
## 50 4
## 53 0
## 54 7
## 55 15
## 57 5
## 59 10
## 60 -3
## 61 8
## 62 68
## 64 0
## 65 0
## 66 8
## 68 3
## 69 0
## 70 23
## 71 -1
## 72 29
## 73 0
## 75 3
## 76 19
## 77 0
## 78 -2
## 80 30
## 81 5
## 82 15
## 83 8
## 84 -1
## 85 1
## 86 14
## 87 1
## 88 4
## 89 39
## 90 2
## 91 -1
## 93 8
## 94 14
## 96 7
## 99 0
## 101 15
## 102 3
## 106 14
## 107 -3
## 109 5
## 110 11
## 111 10
## 112 5
## 113 6
## 116 20
## 117 20
## 118 30
## 119 24
## 120 11
## 122 10
## 123 0
## 124 -3
## 125 17
## 126 20
## 127 13
## 128 0
## 129 28
## 131 52
## 133 5
## 135 6
## 136 37
## 139 -5
## 140 15
## 141 -16
## 142 38
## 143 8
## 144 0
## 145 30
## 147 2
## 148 13
## 149 27
## 151 -2
## 155 10
## 158 27
## 159 -2
## 160 17
## 161 8
## 162 2
## 163 36
## 164 2
## 165 16
## 166 3
## 168 4
## 169 0
## 170 0
## 171 2
## 172 10
## 173 37
## 174 6
## 175 12
## 176 0
## 177 -2
## 179 13
## 180 0
## 181 5
## 182 -5
## 185 0
## 186 5
## 187 20
## 188 8
## 189 12
## 190 8
## 191 14
## 194 33
## 195 -2
## 196 6
## 197 0
## 199 0
## 200 0
## 201 37
## 202 5
## 203 0
## 204 1
## 205 0
## 208 -3
## 211 -2
## 212 23
## 213 0
## 216 18
## 218 7
## 219 3
## 220 11
## 221 2
## 222 0
## 225 -5
## 226 5
## 227 1
## 228 0
##
## $weights
## $weights[[1]]
## [1] 1 1 0 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1
## [35] 0 0 1 0 1 1 0 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 1 1 0 0 0 1 1 0 0 1
## [69] 1 1 0 0 1 1 1 0 0 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 0 1 0 0 0 1 1 1 1 1
## [103] 1 1 1 1 0 1 0 1 1 0 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0
## [137] 0 1 1 0 1 1 1 1 0 0 1 1 0 0 0 1 0 1 1 1 0 1 1 1 0 0
##
## $weights[[2]]
## [1] 1 1 0 0 1 0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 1 1 1 1 1 0 1
## [35] 1 1 1 1 1 1 1 0 1 1 0 1 0 1 1 1 1 0 1 0 0 1 1 0 0 1 1 0 0 1 1 1 1 0
## [69] 0 1 1 1 1 1 1 0 1 1 1 0 1 0 1 1 0 1 0 0 0 1 1 1 1 0 1 0 1 1 1 1 1 0
## [103] 1 1 1 0 1 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 0 1 0 1 0 0 1 1 0 0 1 0 1 0
## [137] 0 0 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 0 0 0 0 1 1 0 1 0
##
## $weights[[3]]
## [1] 1 1 1 0 0 0 0 0 1 0 1 1 1 1 1 0 1 0 0 1 0 0 1 1 1 1 0 1 1 0 1 0 1 1
## [35] 1 0 1 1 1 1 0 1 1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 0 1 0 0 0 0 0 1
## [69] 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 0 1 0 0 0 1 1 1 1 0 0 1 1 1 1 0 1 1
## [103] 1 0 1 1 1 1 0 0 1 0 0 0 0 1 1 0 0 1 0 1 1 1 1 0 1 0 1 1 1 1 1 1 0 1
## [137] 0 1 1 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 1 1 1 1 1
##
## $weights[[4]]
## [1] 1 1 1 1 1 1 0 1 0 0 1 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0 0 0 1 1 0 1 0 1
## [35] 1 0 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 1 1 0 1 1 1 0 1
## [69] 1 0 1 1 1 1 0 0 1 1 1 0 0 1 0 1 0 1 0 1 1 1 1 0 1 0 1 0 1 1 1 1 1 0
## [103] 1 1 0 1 0 1 1 0 0 0 0 1 1 1 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 1 1 1 1 0
## [137] 1 1 0 0 0 0 0 1 1 0 1 1 1 1 0 1 1 1 1 0 0 1 0 0 1 1
##
## $weights[[5]]
## [1] 0 1 1 1 1 1 1 0 1 1 1 0 1 0 1 0 0 1 0 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0
## [35] 1 1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 0 1 1 0 0 0
## [69] 0 1 0 1 1 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 0 1 0 0 0 0 0 1 1 1 1 0
## [103] 0 1 1 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 0 0 1 1 0 1 1 1 1 1 0 0 1 0 1
## [137] 1 1 1 1 1 1 0 0 1 1 0 1 0 1 0 1 1 0 0 1 0 0 1 0 1 0
##
## $weights[[6]]
## [1] 1 1 1 0 0 0 1 1 1 0 0 1 1 1 0 0 1 0 1 1 0 0 0 0 1 1 1 1 0 1 1 0 1 1
## [35] 1 1 0 0 1 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1
## [69] 1 0 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 0 1 0 1 1 1 1 1 0 1 1 0 1 1 0
## [103] 0 0 0 1 1 1 0 0 1 1 0 0 1 1 1 1 1 0 1 1 1 1 0 1 0 0 0 1 0 1 1 1 1 1
## [137] 1 0 1 1 0 1 1 1 0 0 1 0 1 0 0 0 1 0 1 1 0 1 1 1 0 0
##
## $weights[[7]]
## [1] 0 0 1 1 1 1 1 1 0 1 1 1 1 1 0 1 0 0 1 0 1 1 1 1 0 0 1 0 1 0 1 0 1 0
## [35] 0 0 1 0 1 1 1 1 1 0 0 1 1 1 0 1 0 0 0 1 1 0 0 1 1 1 1 1 0 0 1 1 1 0
## [69] 1 1 1 0 0 1 0 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 0 1 0 1 0 1 1 1 1 1 1
## [103] 1 1 1 0 1 0 1 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 0 1 0 1 1 0 1 1 0 1 1 1
## [137] 1 1 0 1 1 0 1 1 0 0 1 1 0 0 1 1 0 1 1 0 1 0 1 1 1 1
##
## $weights[[8]]
## [1] 0 1 1 1 1 0 1 1 0 1 0 1 1 0 0 1 0 1 0 0 1 1 1 0 1 0 1 1 1 0 0 1 0 1
## [35] 1 0 0 1 0 0 1 0 0 1 0 0 1 1 0 0 1 1 1 0 1 1 1 1 1 0 0 1 0 0 0 1 0 0
## [69] 1 1 1 1 1 1 1 1 0 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0 1
## [103] 0 0 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 0 1 1 0 1 0 1 1 1 1 0 1 1 1 0
## [137] 1 0 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 0 0 0 1 1 1 1
##
## $weights[[9]]
## [1] 1 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 0
## [35] 1 1 1 0 1 0 1 1 0 0 1 1 1 1 0 1 0 0 0 0 1 1 1 1 0 0 0 1 1 1 1 1 0 1
## [69] 0 1 1 0 1 1 1 1 1 1 0 1 0 0 1 0 0 0 0 0 1 1 1 0 1 1 1 1 1 0 1 1 0 0
## [103] 1 1 0 0 1 1 0 0 1 0 1 1 1 1 0 0 1 1 0 1 1 0 1 0 0 1 1 0 0 1 1 0 0 1
## [137] 1 1 1 0 1 0 0 1 1 1 1 1 1 0 1 1 1 0 0 1 0 0 0 1 0 0
##
## $weights[[10]]
## [1] 1 0 0 1 0 0 1 1 1 1 1 0 1 1 0 1 1 1 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0
## [35] 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 0 1
## [69] 0 0 1 0 0 1 1 1 0 1 0 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 1 1 1 1 0 0 1 0
## [103] 0 1 1 0 1 1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 1 0 1 1 0 1 1 1 1 0 0 1 1 0
## [137] 1 0 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 0 1 0 0 0 0 0 1
##
## $weights[[11]]
## [1] 0 1 0 1 1 0 1 0 1 1 1 0 1 0 1 1 0 0 1 0 1 1 1 1 0 0 1 0 1 0 0 1 1 0
## [35] 0 1 1 0 1 0 0 1 1 1 0 1 1 1 1 0 1 0 1 1 1 1 0 0 0 1 0 1 0 1 0 1 1 1
## [69] 1 0 1 0 1 1 1 1 0 0 1 1 1 1 1 0 1 1 1 0 0 1 1 0 1 0 1 1 1 0 1 0 0 0
## [103] 0 1 1 0 0 0 1 0 0 1 1 1 1 1 1 1 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 1 0 1
## [137] 1 1 1 0 1 1 1 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1 1 1 0
##
## $weights[[12]]
## [1] 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 1 1 1 0 1 0 1 0 1 1 1 1 0 1 0 1 1 1 0
## [35] 0 0 1 1 1 0 1 1 0 0 0 1 1 0 1 1 1 0 1 0 0 0 1 1 0 1 0 0 0 1 0 1 1 0
## [69] 1 1 1 1 0 0 1 0 0 0 1 0 1 0 1 1 1 1 0 0 1 0 0 0 0 1 1 1 1 1 1 1 1 1
## [103] 1 1 1 0 0 1 1 0 0 1 1 1 1 0 0 1 1 1 1 1 0 0 1 1 1 1 0 0 1 1 1 0 0 1
## [137] 0 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 1 1 1 1 1 0 1 1 0 1
##
## $weights[[13]]
## [1] 0 1 0 0 1 1 1 1 1 1 1 0 1 0 1 1 0 0 0 1 1 1 0 1 1 0 1 0 0 1 0 0 1 1
## [35] 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 1 1 0 0 0 1 1 0 1 0 1 0 1 1 1
## [69] 0 1 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 1 0 1 1 1 1 0 0 1 1 1 0 1 0 0 1
## [103] 0 1 0 0 1 1 1 0 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1
## [137] 1 1 1 1 1 0 1 0 1 0 1 1 1 1 0 1 1 1 0 0 1 1 1 0 1 1
##
## $weights[[14]]
## [1] 0 1 1 1 1 1 0 1 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 0 0 1
## [35] 1 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 1 1 1
## [69] 1 1 0 1 1 1 0 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 1 0
## [103] 1 1 1 1 1 0 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 0 0 1 1 0 1 0 0 1
## [137] 1 1 0 0 0 1 1 1 1 1 0 1 1 1 0 0 1 0 1 1 0 0 0 0 1 0
##
## $weights[[15]]
## [1] 0 1 0 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1
## [35] 1 0 0 1 0 0 1 1 0 1 0 1 0 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1 0 1
## [69] 1 0 1 1 0 0 0 1 1 1 0 1 1 1 1 0 0 1 1 0 1 1 0 1 1 0 1 1 1 0 1 0 0 1
## [103] 1 1 1 0 0 1 1 0 1 1 0 0 0 0 0 0 0 1 0 1 0 1 1 1 0 1 0 1 1 0 1 0 0 1
## [137] 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 1 0 1
##
## $weights[[16]]
## [1] 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 1 0 1 1 0 1 1 0 1 1 0 0 1 1 1 1 1 0 0
## [35] 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 1
## [69] 1 0 1 0 1 0 1 1 1 0 1 0 0 1 0 1 1 0 1 1 1 1 1 0 0 0 1 0 0 1 1 1 1 1
## [103] 0 0 1 1 0 1 0 1 1 0 0 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 0 0 1 0
## [137] 1 1 1 1 0 0 1 0 1 1 1 1 1 0 0 1 1 1 0 1 0 0 0 1 1 0
##
## $weights[[17]]
## [1] 1 1 1 0 1 0 1 0 1 1 0 1 0 1 1 1 1 0 0 0 1 0 0 1 0 1 1 1 1 1 0 1 0 1
## [35] 0 1 1 0 1 0 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 0 0 1 0 1 0 1 1 1 0 1 1
## [69] 1 1 0 0 1 1 1 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 1 1 1 0 1 1 0 1 1 1 0 1
## [103] 0 1 1 1 1 1 1 1 0 1 1 1 0 0 0 0 1 0 0 1 0 0 0 1 0 1 1 1 0 0 0 1 1 0
## [137] 1 1 0 1 1 0 0 0 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 1 1 0
##
## $weights[[18]]
## [1] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 0 1 1 0 0 1 0 0 1 1 0 1 0 0 0 1 1 1 1
## [35] 1 0 1 1 1 1 1 0 0 0 1 0 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 1 1 0
## [69] 0 0 0 1 0 0 1 1 0 1 1 1 0 1 1 0 1 1 1 1 1 0 1 0 1 0 1 0 1 1 0 1 1 0
## [103] 1 1 1 1 1 0 0 1 0 0 1 1 1 1 1 1 1 0 1 1 0 1 0 0 1 1 1 0 0 1 1 1 1 0
## [137] 1 0 0 1 0 1 1 0 1 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 1 0
##
## $weights[[19]]
## [1] 1 0 0 1 0 0 0 0 0 1 0 1 1 1 0 1 1 0 1 1 0 1 0 1 0 1 1 1 0 1 1 0 1 0
## [35] 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 0 1 1 0 0 1 0 1 0 0 1 1 1 1 0 0 1 1 1
## [69] 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 1 0 1 1 1 0 1
## [103] 1 0 1 0 1 1 0 0 0 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1
## [137] 1 1 1 1 1 0 1 1 1 0 0 1 1 0 1 0 1 1 1 0 0 0 1 1 0 0
##
## $weights[[20]]
## [1] 1 1 0 1 1 0 0 0 0 1 0 0 0 1 0 1 1 1 1 0 1 0 1 0 0 0 0 1 1 0 1 1 0 0
## [35] 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 1 1 0 1 1 0 1 0 1 0 1 0 0
## [69] 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1
## [103] 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 0 1 1 1
## [137] 0 0 0 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 0 1 1 0 1 0
##
## $weights[[21]]
## [1] 0 1 1 1 0 1 0 1 1 1 0 1 0 1 0 0 1 0 1 1 1 1 1 0 1 1 1 1 1 1 0 1 0 1
## [35] 0 1 1 0 1 0 1 1 0 0 1 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 0 0 0
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## [137] 1 0 1 0 0 0 1 0 0 0 1 1 0 1 0 1 1 1 1 0 1 0 1 1 0 1
##
## $weights[[22]]
## [1] 1 0 1 0 1 0 1 1 0 1 0 1 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0
## [35] 1 1 0 0 0 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 1 0 0
## [69] 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 0 1 1 1 0 1 1 0 1 1 0 1 0 1 0 1
## [103] 1 1 1 1 0 0 1 1 1 1 1 0 1 0 1 0 0 0 1 1 1 1 0 0 1 0 1 0 0 1 1 0 1 1
## [137] 0 0 1 0 0 1 0 0 1 0 1 0 0 0 1 0 0 0 1 0 0 1 1 1 1 0
##
## $weights[[23]]
## [1] 1 0 0 1 0 1 1 1 0 1 0 1 0 1 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 0
## [35] 1 0 0 1 0 1 1 1 1 1 1 1 0 0 0 0 1 1 0 1 0 0 0 0 1 1 1 0 1 0 0 1 0 1
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## [137] 1 0 1 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1 1 1 1 0 1
##
## $weights[[24]]
## [1] 0 0 1 1 1 1 0 1 1 0 1 0 1 1 0 0 1 1 0 1 1 1 1 0 1 1 1 1 0 0 1 1 1 1
## [35] 1 1 1 0 0 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 0 1 1 1
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## [137] 0 0 0 1 1 1 1 0 1 0 1 0 1 1 1 0 1 0 1 1 1 0 1 0 1 1
##
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## $weights[[200]]
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##
##
## $fitted
## idx (response)
## 1 1 218
## 2 2 166
## 3 3 170
## 4 4 567
## 5 5 613
## 6 6 707
## 7 7 61
## 8 8 301
## 9 9 81
## 10 10 371
## 11 11 520
## 12 12 574
## 13 13 118
## 14 14 390
## 15 15 12
## 16 16 473
## 17 17 26
## 18 18 107
## 19 19 53
## 20 20 814
## 21 21 965+
## 22 22 93
## 23 23 731
## 24 24 460
## 25 25 153
## 26 26 433
## 27 27 583
## 28 28 95
## 29 29 303
## 30 30 519
## 31 31 643
## 32 32 765
## 33 33 53
## 34 34 246
## 35 35 689
## 36 36 5
## 37 37 687
## 38 38 345
## 39 39 444
## 40 40 223
## 41 41 60
## 42 42 163
## 43 43 65
## 44 44 821+
## 45 45 428
## 46 46 230
## 47 47 840+
## 48 48 305
## 49 49 11
## 50 50 226
## 51 51 426
## 52 52 705
## 53 53 363
## 54 54 176
## 55 55 791
## 56 56 95
## 57 57 196+
## 58 58 167
## 59 59 806+
## 60 60 284
## 61 61 641
## 62 62 147
## 63 63 740+
## 64 64 163
## 65 65 655
## 66 66 88
## 67 67 245
## 68 68 30
## 69 69 477
## 70 70 559+
## 71 71 450
## 72 72 156
## 73 73 529+
## 74 74 429
## 75 75 351
## 76 76 15
## 77 77 181
## 78 78 283
## 79 79 13
## 80 80 212
## 81 81 524
## 82 82 288
## 83 83 363
## 84 84 199
## 85 85 550
## 86 86 54
## 87 87 558
## 88 88 207
## 89 89 92
## 90 90 60
## 91 91 551+
## 92 92 293
## 93 93 353
## 94 94 267
## 95 95 511+
## 96 96 457
## 97 97 337
## 98 98 201
## 99 99 404+
## 100 100 222
## 101 101 62
## 102 102 458+
## 103 103 353
## 104 104 163
## 105 105 31
## 106 106 229
## 107 107 156
## 108 108 291
## 109 109 179
## 110 110 376+
## 111 111 384+
## 112 112 268
## 113 113 292+
## 114 114 142
## 115 115 413+
## 116 116 266+
## 117 117 320
## 118 118 181
## 119 119 285
## 120 120 301+
## 121 121 348
## 122 122 197
## 123 123 382+
## 124 124 303+
## 125 125 296+
## 126 126 180
## 127 127 145
## 128 128 269+
## 129 129 300+
## 130 130 284+
## 131 131 292+
## 132 132 332+
## 133 133 285
## 134 134 259+
## 135 135 110
## 136 136 286
## 137 137 270
## 138 138 225+
## 139 139 269
## 140 140 225+
## 141 141 243+
## 142 142 276+
## 143 143 135
## 144 144 79
## 145 145 59
## 146 146 240+
## 147 147 202+
## 148 148 235+
## 149 149 239
## 150 150 252+
## 151 151 221+
## 152 152 185+
## 153 153 222+
## 154 154 183
## 155 155 211+
## 156 156 175+
## 157 157 197+
## 158 158 203+
## 159 159 191+
## 160 160 105+
## 161 161 174+
## 162 162 177+
##
## $terms
## Surv(time, status) ~ inst + age + sex + ph.ecog + ph.karno +
## pat.karno + meal.cal + wt.loss
## attr(,"variables")
## list(Surv(time, status), inst, age, sex, ph.ecog, ph.karno, pat.karno,
## meal.cal, wt.loss)
## attr(,"factors")
## inst age sex ph.ecog ph.karno pat.karno meal.cal
## Surv(time, status) 0 0 0 0 0 0 0
## inst 1 0 0 0 0 0 0
## age 0 1 0 0 0 0 0
## sex 0 0 1 0 0 0 0
## ph.ecog 0 0 0 1 0 0 0
## ph.karno 0 0 0 0 1 0 0
## pat.karno 0 0 0 0 0 1 0
## meal.cal 0 0 0 0 0 0 1
## wt.loss 0 0 0 0 0 0 0
## wt.loss
## Surv(time, status) 0
## inst 0
## age 0
## sex 0
## ph.ecog 0
## ph.karno 0
## pat.karno 0
## meal.cal 0
## wt.loss 1
## attr(,"term.labels")
## [1] "inst" "age" "sex" "ph.ecog" "ph.karno"
## [6] "pat.karno" "meal.cal" "wt.loss"
## attr(,"order")
## [1] 1 1 1 1 1 1 1 1
## attr(,"intercept")
## [1] 1
## attr(,"response")
## [1] 1
## attr(,".Environment")
## <environment: 0x563ee5083770>
## attr(,"Formula_with_dot")
## Surv(time, status) ~ .
## <environment: 0x563ee5083770>
## attr(,"Formula_without_dot")
## Surv(time, status) ~ inst + age + sex + ph.ecog + ph.karno +
## pat.karno + meal.cal + wt.loss
## <environment: 0x563ee5083770>
## attr(,"dot")
## [1] "sequential"
##
## $info
## $info$call
## partykit::cforest(formula = formula, data = data, weights = weights,
## control = partykit::ctree_control(minsplit = 20L, maxdepth = Inf,
## teststat = "quadratic", testtype = "Univariate", mincriterion = 0,
## saveinfo = FALSE), ntree = 200, mtry = 3)
##
## $info$control
## $info$control$criterion
## [1] "p.value"
##
## $info$control$logmincriterion
## [1] -Inf
##
## $info$control$minsplit
## [1] 20
##
## $info$control$minbucket
## [1] 7
##
## $info$control$minprob
## [1] 0.01
##
## $info$control$maxvar
## [1] Inf
##
## $info$control$stump
## [1] FALSE
##
## $info$control$nmax
## yx z
## Inf Inf
##
## $info$control$lookahead
## [1] FALSE
##
## $info$control$mtry
## [1] 3
##
## $info$control$maxdepth
## [1] Inf
##
## $info$control$multiway
## [1] FALSE
##
## $info$control$splittry
## [1] 2
##
## $info$control$maxsurrogate
## [1] 0
##
## $info$control$numsurrogate
## [1] FALSE
##
## $info$control$majority
## [1] FALSE
##
## $info$control$caseweights
## [1] TRUE
##
## $info$control$applyfun
## function (X, FUN, ...)
## {
## FUN <- match.fun(FUN)
## if (!is.vector(X) || is.object(X))
## X <- as.list(X)
## .Internal(lapply(X, FUN))
## }
## <bytecode: 0x563ed0f23c40>
## <environment: namespace:base>
##
## $info$control$saveinfo
## [1] FALSE
##
## $info$control$bonferroni
## [1] FALSE
##
## $info$control$update
## [1] FALSE
##
## $info$control$selectfun
## function (model, trafo, data, subset, weights, whichvar, ctrl)
## {
## args <- list(...)
## ctrl[names(args)] <- args
## .select(model, trafo, data, subset, weights, whichvar, ctrl,
## FUN = .ctree_test)
## }
## <bytecode: 0x563ee343af30>
## <environment: 0x563ee124de68>
##
## $info$control$splitfun
## function (model, trafo, data, subset, weights, whichvar, ctrl)
## {
## args <- list(...)
## ctrl[names(args)] <- args
## .split(model, trafo, data, subset, weights, whichvar, ctrl,
## FUN = .ctree_test)
## }
## <bytecode: 0x563ee343d160>
## <environment: 0x563ee1248bf8>
##
## $info$control$svselectfun
## function (model, trafo, data, subset, weights, whichvar, ctrl)
## {
## args <- list(...)
## ctrl[names(args)] <- args
## .select(model, trafo, data, subset, weights, whichvar, ctrl,
## FUN = .ctree_test)
## }
## <bytecode: 0x563ee343af30>
## <environment: 0x563ee1248cd8>
##
## $info$control$svsplitfun
## function (model, trafo, data, subset, weights, whichvar, ctrl)
## {
## args <- list(...)
## ctrl[names(args)] <- args
## .split(model, trafo, data, subset, weights, whichvar, ctrl,
## FUN = .ctree_test)
## }
## <bytecode: 0x563ee343d160>
## <environment: 0x563ee1248d48>
##
## $info$control$teststat
## [1] "quadratic"
##
## $info$control$splitstat
## [1] "quadratic"
##
## $info$control$splittest
## [1] FALSE
##
## $info$control$pargs
## $maxpts
## [1] 25000
##
## $abseps
## [1] 0.001
##
## $releps
## [1] 0
##
## attr(,"class")
## [1] "GenzBretz"
##
## $info$control$testtype
## [1] "Univariate"
##
## $info$control$nresample
## [1] 9999
##
## $info$control$tol
## [1] 1.490116e-08
##
## $info$control$intersplit
## [1] FALSE
##
## $info$control$MIA
## [1] FALSE
##
##
##
## $trafo
## function (subset, weights, info, estfun, object, ...)
## list(estfun = Y, unweighted = TRUE)
## <bytecode: 0x563ee01e0830>
## <environment: 0x563ee123b988>
##
## $predictf
## ~inst + age + sex + ph.ecog + ph.karno + pat.karno + meal.cal +
## wt.loss
## attr(,"variables")
## list(inst, age, sex, ph.ecog, ph.karno, pat.karno, meal.cal,
## wt.loss)
## attr(,"factors")
## inst age sex ph.ecog ph.karno pat.karno meal.cal wt.loss
## inst 1 0 0 0 0 0 0 0
## age 0 1 0 0 0 0 0 0
## sex 0 0 1 0 0 0 0 0
## ph.ecog 0 0 0 1 0 0 0 0
## ph.karno 0 0 0 0 1 0 0 0
## pat.karno 0 0 0 0 0 1 0 0
## meal.cal 0 0 0 0 0 0 1 0
## wt.loss 0 0 0 0 0 0 0 1
## attr(,"term.labels")
## [1] "inst" "age" "sex" "ph.ecog" "ph.karno"
## [6] "pat.karno" "meal.cal" "wt.loss"
## attr(,"order")
## [1] 1 1 1 1 1 1 1 1
## attr(,"intercept")
## [1] 1
## attr(,"response")
## [1] 0
## attr(,".Environment")
## <environment: 0x563ee5083770>
## attr(,"Formula_with_dot")
## Surv(time, status) ~ .
## <environment: 0x563ee5083770>
## attr(,"Formula_without_dot")
## Surv(time, status) ~ inst + age + sex + ph.ecog + ph.karno +
## pat.karno + meal.cal + wt.loss
## <environment: 0x563ee5083770>
## attr(,"dot")
## [1] "sequential"
##
## attr(,"class")
## [1] "cforest" "constparties" "parties"The holdout data can be predicted for survival probability at different time points as well as event time.
predict(
rf_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.886
## 2 500 0.303
## 3 1000 0.0443
predict(rf_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 337
## 2 267
## 3 230
## 4 201
## 5 226
With the "aorsf" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
rf_spec <-
rand_forest(trees = 200) %>%
set_engine("aorsf") %>%
set_mode("censored regression")
rf_spec ## Random Forest Model Specification (censored regression)
##
## Main Arguments:
## trees = 200
##
## Computational engine: aorsfNow we create the model fit object:
## parsnip model object
##
## ---------- Oblique random survival forest
##
## Linear combinations: Accelerated Cox regression
## N observations: 162
## N events: 278
## N trees: 200
## N predictors total: 8
## N predictors per node: 3
## Average leaves per tree: 17.175
## Min observations in leaf: 5
## Min events in leaf: 1
## OOB stat value: 0.62
## OOB stat type: Harrell's C-index
## Variable importance: anova
##
## -----------------------------------------The holdout data can be predicted for survival probability at different time points as well as event time.
predict(
rf_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.917
## 2 500 0.397
## 3 1000 0.0538
predict(rf_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 397.
## 2 277.
## 3 240.
## 4 228.
## 5 226.
survival_reg() models
With the "survival" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
sr_spec <-
survival_reg(dist = "weibull") %>%
set_engine("survival") %>%
set_mode("censored regression")
sr_spec ## Parametric Survival Regression Model Specification (censored regression)
##
## Main Arguments:
## dist = weibull
##
## Computational engine: survivalNow we create the model fit object:
## parsnip model object
##
## Call:
## survival::survreg(formula = Surv(time, status) ~ ., data = data,
## dist = ~"weibull", model = TRUE)
##
## Coefficients:
## (Intercept) inst age sex ph.ecog
## 6.2802499155 0.0191302849 -0.0085917372 0.4249655608 -0.5022975982
## ph.karno pat.karno meal.cal wt.loss
## -0.0085852225 0.0058753359 0.0001003211 0.0127001420
##
## Scale= 0.6902035
##
## Loglik(model)= -795.2 Loglik(intercept only)= -811.4
## Chisq= 32.41 on 8 degrees of freedom, p= 7.85e-05
## n= 162The holdout data can be predicted for survival probability at different time points as well as event time, linear predictor, quantile, and hazard.
predict(
sr_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.912
## 2 500 0.386
## 3 1000 0.0742
predict(sr_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 517.
## 2 283.
## 3 361.
## 4 268.
## 5 313.
predict(sr_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 6.25
## 2 5.64
## 3 5.89
## 4 5.59
## 5 5.75 ## # A tibble: 9 × 2
## .quantile .pred_quantile
## <dbl> <dbl>
## 1 0.1 109.
## 2 0.2 184.
## 3 0.3 254.
## 4 0.4 325.
## 5 0.5 401.
## 6 0.6 487.
## 7 0.7 588.
## 8 0.8 718.
## 9 0.9 919.
predict(sr_fit, lung_test, type = "hazard", eval_time = c(100, 500, 1000)) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_hazard
## <dbl> <dbl>
## 1 100 0.00134
## 2 500 0.00276
## 3 1000 0.00377
With the "flexsurv" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model with specific parameters:
sr_spec <-
survival_reg(dist = "weibull") %>%
set_engine("flexsurv") %>%
set_mode("censored regression")
sr_spec ## Parametric Survival Regression Model Specification (censored regression)
##
## Main Arguments:
## dist = weibull
##
## Computational engine: flexsurvNow we create the model fit object:
set.seed(1)
sr_fit <- sr_spec %>%
fit(Surv(time, status) ~ age + sex + ph.ecog, data = lung_train)
sr_fit ## parsnip model object
##
## Call:
## flexsurv::flexsurvreg(formula = Surv(time, status) ~ age + sex +
## ph.ecog, data = data, dist = ~"weibull")
##
## Estimates:
## data mean est L95% U95% se exp(est)
## shape NA 1.39e+00 1.21e+00 1.61e+00 1.02e-01 NA
## scale NA 5.74e+02 1.99e+02 1.65e+03 3.10e+02 NA
## age 6.24e+01 -9.02e-03 -2.50e-02 6.95e-03 8.15e-03 9.91e-01
## sex 1.38e+00 4.02e-01 1.17e-01 6.87e-01 1.45e-01 1.50e+00
## ph.ecog 9.51e-01 -3.17e-01 -5.13e-01 -1.21e-01 1.00e-01 7.28e-01
## L95% U95%
## shape NA NA
## scale NA NA
## age 9.75e-01 1.01e+00
## sex 1.12e+00 1.99e+00
## ph.ecog 5.99e-01 8.86e-01
##
## N = 162, Events: 116, Censored: 46
## Total time at risk: 49401
## Log-likelihood = -800.356, df = 5
## AIC = 1610.712The holdout data can be predicted for survival probability at different time points as well as event time, linear predictor, quantile, and hazard.
predict(
sr_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.889
## 2 500 0.330
## 3 1000 0.0543
predict(sr_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 424.
## 2 341.
## 3 292.
## 4 336.
## 5 327.
predict(sr_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 6.14
## 2 5.92
## 3 5.77
## 4 5.91
## 5 5.88 ## # A tibble: 9 × 2
## .quantile .pred_quantile
## <dbl> <dbl>
## 1 0.1 92.5
## 2 0.2 158.
## 3 0.3 222.
## 4 0.4 287.
## 5 0.5 357.
## 6 0.6 436.
## 7 0.7 531.
## 8 0.8 653.
## 9 0.9 845.
predict(sr_fit, lung_test, type = "hazard", eval_time = c(100, 500, 1000)) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_hazard
## <dbl> <dbl>
## 1 100 0.00164
## 2 500 0.00309
## 3 1000 0.00406
With the "flexsurvspline" engine
We’ll model the survival of lung cancer patients.
library(tidymodels)
library(censored)
tidymodels_prefer()
data(cancer)
lung <- lung %>% drop_na()
lung_train <- lung[-c(1:5), ]
lung_test <- lung[1:5, ]We can define the model:
sr_spec <-
survival_reg() %>%
set_engine("flexsurvspline") %>%
set_mode("censored regression")
sr_spec ## Parametric Survival Regression Model Specification (censored regression)
##
## Computational engine: flexsurvsplineNow we create the model fit object:
set.seed(1)
sr_fit <- sr_spec %>%
fit(Surv(time, status) ~ age + sex + ph.ecog, data = lung_train)
sr_fit ## parsnip model object
##
## Call:
## flexsurv::flexsurvspline(formula = Surv(time, status) ~ age +
## sex + ph.ecog, data = data)
##
## Estimates:
## data mean est L95% U95% se exp(est)
## gamma0 NA -8.85681 -10.78595 -6.92767 0.98427 NA
## gamma1 NA 1.39431 1.19358 1.59504 0.10241 NA
## age 62.41358 0.01258 -0.00968 0.03484 0.01136 1.01266
## sex 1.38272 -0.56080 -0.95517 -0.16643 0.20121 0.57075
## ph.ecog 0.95062 0.44213 0.17197 0.71230 0.13784 1.55602
## L95% U95%
## gamma0 NA NA
## gamma1 NA NA
## age 0.99037 1.03545
## sex 0.38475 0.84668
## ph.ecog 1.18764 2.03867
##
## N = 162, Events: 116, Censored: 46
## Total time at risk: 49401
## Log-likelihood = -800.356, df = 5
## AIC = 1610.712The holdout data can be predicted for survival probability at different time points as well as event time, linear predictor, quantile, and hazard.
predict(
sr_fit,
lung_test,
type = "survival",
eval_time = c(100, 500, 1000)
) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_survival
## <dbl> <dbl>
## 1 100 0.889
## 2 500 0.330
## 3 1000 0.0543
predict(sr_fit, lung_test, type = "time") ## # A tibble: 5 × 1
## .pred_time
## <dbl>
## 1 424.
## 2 341.
## 3 292.
## 4 336.
## 5 327.
predict(sr_fit, lung_test, type = "linear_pred") ## # A tibble: 5 × 1
## .pred_linear_pred
## <dbl>
## 1 -8.56
## 2 -8.26
## 3 -8.04
## 4 -8.24
## 5 -8.20 ## # A tibble: 9 × 2
## .quantile .pred_quantile
## <dbl> <dbl>
## 1 0.1 92.5
## 2 0.2 158.
## 3 0.3 222.
## 4 0.4 287.
## 5 0.5 357.
## 6 0.6 436.
## 7 0.7 531.
## 8 0.8 653.
## 9 0.9 845.
predict(sr_fit, lung_test, type = "hazard", eval_time = c(100, 500, 1000)) %>%
slice(1) %>%
tidyr::unnest(col = .pred) ## # A tibble: 3 × 2
## .eval_time .pred_hazard
## <dbl> <dbl>
## 1 100 0.00164
## 2 500 0.00309
## 3 1000 0.00406