mlpack (version 4.8.0)

decision_tree_probabilities: Decision tree Prediction

Description

Class predictions from train decision tree model.

Usage

decision_tree_probabilities(
  input_model,
  test,
  test_labels = NA,
  verbose = getOption("mlpack.verbose", FALSE)
)

Value

A list with several components defining the class attributes:

probabilities

Class probabilities for each test point if probabilities has been selected (numeric matrix).

Arguments

input_model

Pre-trained decision tree, to be used with test points (DecisionTreeModel).

test

Testing dataset (may contain categorical variables) (numeric matrix/data.frame with info).

test_labels

Test point labels, if accuracy calculation is desired (integer row).

verbose

Display informational messages and the full list of parameters and timers at the end of execution. Default value "getOption("mlpack.verbose", FALSE)" (logical).

Author

mlpack developers

Examples

# \dontrun{ prob <- predict(model, newdata=X_test, type="probabilities") }