mlpack (version 4.8.0)

decision_tree_classify: Decision tree Prediction

Description

Class predictions from train decision tree model.

Usage

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

Value

A list with several components defining the class attributes:

predictions

Class predictions for each test point (integer row).

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{ pred <- predict(model, newdata=X_test) }