Classification J48 Learner
mlr_learners_classif.J48.Rd
Decision tree algorithm.
Calls RWeka::IBk()
from RWeka.
Meta Information
Task type: “classif”
Predict Types: “response”, “prob”
Feature Types: “integer”, “numeric”, “factor”, “ordered”
Required Packages: mlr3, mlr3extralearners, RWeka
Parameters
Id | Type | Default | Levels | Range |
subset | untyped | - | - | |
na.action | untyped | - | - | |
U | logical | FALSE | TRUE, FALSE | - |
O | logical | FALSE | TRUE, FALSE | - |
C | numeric | 0.25 | \([2.22044604925031e-16, 1]\) | |
M | integer | 2 | \([1, \infty)\) | |
R | logical | FALSE | TRUE, FALSE | - |
N | integer | 3 | \([2, \infty)\) | |
B | logical | FALSE | TRUE, FALSE | - |
S | logical | FALSE | TRUE, FALSE | - |
L | logical | FALSE | TRUE, FALSE | - |
A | logical | FALSE | TRUE, FALSE | - |
J | logical | FALSE | TRUE, FALSE | - |
Q | integer | 1 | \([1, \infty)\) | |
doNotMakeSplitPointActualValue | logical | FALSE | TRUE, FALSE | - |
output_debug_info | logical | FALSE | TRUE, FALSE | - |
do_not_check_capabilities | logical | FALSE | TRUE, FALSE | - |
num_decimal_places | integer | 2 | \([1, \infty)\) | |
batch_size | integer | 100 | \([1, \infty)\) | |
options | untyped | NULL | - |
Custom mlr3 parameters
output_debug_info
:original id: output-debug-info
do_not_check_capabilities
:original id: do-not-check-capabilities
num_decimal_places
:original id: num-decimal-places
batch_size
:original id: batch-size
Reason for change: This learner contains changed ids of the following control arguments since their ids contain irregular pattern
See also
as.data.table(mlr_learners)
for a table of available Learners in the running session (depending on the loaded packages).Chapter in the mlr3book: https://mlr3book.mlr-org.com/basics.html#learners
mlr3learners for a selection of recommended learners.
mlr3cluster for unsupervised clustering learners.
mlr3pipelines to combine learners with pre- and postprocessing steps.
mlr3tuning for tuning of hyperparameters, mlr3tuningspaces for established default tuning spaces.
Super classes
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifJ48
Examples
# Define the Learner
learner = mlr3::lrn("classif.J48")
print(learner)
#>
#> ── <LearnerClassifJ48> (classif.J48): Tree-based Model ─────────────────────────
#> • Model: -
#> • Parameters: list()
#> • Packages: mlr3, mlr3extralearners, and RWeka
#> • Predict Types: [response] and prob
#> • Feature Types: integer, numeric, factor, and ordered
#> • Encapsulation: none (fallback: -)
#> • Properties: missings, multiclass, and twoclass
#> • Other settings: use_weights = 'error'
# Define a Task
task = mlr3::tsk("sonar")
# Create train and test set
ids = mlr3::partition(task)
# Train the learner on the training ids
learner$train(task, row_ids = ids$train)
print(learner$model)
#> J48 pruned tree
#> ------------------
#>
#> V11 <= 0.1109: R (28.0/1.0)
#> V11 > 0.1109
#> | V54 <= 0.0205
#> | | V9 <= 0.116
#> | | | V23 <= 0.8067: R (18.0/1.0)
#> | | | V23 > 0.8067: M (3.0)
#> | | V9 > 0.116
#> | | | V47 <= 0.0365: R (6.0)
#> | | | V47 > 0.0365
#> | | | | V28 <= 0.808
#> | | | | | V11 <= 0.3412
#> | | | | | | V15 <= 0.499
#> | | | | | | | V37 <= 0.4827: M (12.0/1.0)
#> | | | | | | | V37 > 0.4827: R (5.0)
#> | | | | | | V15 > 0.499: R (12.0)
#> | | | | | V11 > 0.3412: M (9.0)
#> | | | | V28 > 0.808: M (30.0)
#> | V54 > 0.0205: M (16.0)
#>
#> Number of Leaves : 10
#>
#> Size of the tree : 19
#>
# Make predictions for the test rows
predictions = learner$predict(task, row_ids = ids$test)
# Score the predictions
predictions$score()
#> classif.ce
#> 0.2463768