dec.tree.class.fit: Fit a decision tree classifier.

In ebridge2/badmf: Bayesian Decision-Making Forests (BaD-MFs)

Description

Fit a decision tree classifier.

Usage

dec.tree.class.fit(X, Y, d = NULL, alpha = NULL, depth.max = 5L,
  size = 1L, debug = FALSE)

Arguments

X	the predictors. A [n, p] matrix.
Y	the responses. A [n] vector or, optionally, a factor.
d	the number of features to subsample at each node. Defaults to NULL, which tries every feature.
alpha	the prior parameters for the feature probabilities. A [p] vector. If NULL, samples uniformly. Defaults to NULL.
depth.max	the maximum allowed tree depth. Defaults to 5L.
size	the minimum allowed number of samples for an individual node. Defaults to 1L.
debug	whether to save the predictors and responses that are categorized. Defaults to FALSE. into a particular leaf node.

Value

an object of class dec.tree.class containing the following:

tree	the decision tree.
X	The training predictors.
Y	the training responses.
d	d the number of features subsampled at each node.
alpha	the sampling distribution for the features. A [p] vector.
depth.max	the maximum allowed tree depth.
size	the maximum allowed tree depth.
debug	whether to save the predictors and responses that are categorized.

Author(s)

Eric Bridgeford

ebridge2/badmf documentation built on June 4, 2019, 8:53 a.m.