mlpack::tree::InformationGain Class Reference

The standard information gain criterion, used for calculating gain in decision trees. More...

Static Public Member Functions
static double	Evaluate (const arma::Mat< size_t > &counts)
	Given the sufficient statistics of a proposed split, calculate the information gain if that split was to be used. More...
static double	Evaluate (const arma::Row< size_t > &labels, const size_t numClasses)
	Given a set of labels, calculate the information gain of those labels. More...
static double	Range (const size_t numClasses)
	Return the range of the information gain for the given number of classes. More...
static double	Range (const size_t numClasses)
	Return the range of the information gain for the given number of classes. More...

Detailed Description

The standard information gain criterion, used for calculating gain in decision trees.

Definition at line 25 of file information_gain.hpp.

Member Function Documentation

static double mlpack::tree::InformationGain::Evaluate ( const arma::Mat< size_t > &  counts )

inlinestatic

Given the sufficient statistics of a proposed split, calculate the information gain if that split was to be used.

The 'counts' matrix should contain the number of points in each class in each column, so the size of 'counts' is children x classes, where 'children' is the number of child nodes in the proposed split.

Parameters

counts

Matrix of sufficient statistics.

Definition at line 31 of file information_gain.hpp.

static double mlpack::tree::InformationGain::Evaluate ( const arma::Row< size_t > &  labels, const size_t  numClasses  )

inlinestatic

Given a set of labels, calculate the information gain of those labels.

Parameters

labels	Labels of the dataset.
numClasses	Number of classes in the dataset.

Definition at line 34 of file information_gain.hpp.

static double mlpack::tree::InformationGain::Range ( const size_t  numClasses )

inlinestatic

Return the range of the information gain for the given number of classes.

(That is, the difference between the maximum possible value and the minimum possible value.)

Parameters

numClasses

Number of classes in the dataset.

Definition at line 66 of file information_gain.hpp.

static double mlpack::tree::InformationGain::Range ( const size_t  numClasses )

inlinestatic

Return the range of the information gain for the given number of classes.

(That is, the difference between the maximum possible value and the minimum possible value.)

Definition at line 84 of file information_gain.hpp.

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The documentation for this class was generated from the following file:

• src/mlpack/methods/decision_tree/information_gain.hpp