org.tribuo.classification.dtree.impurity

Interface LabelImpurity

All Superinterfaces:

com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>

All Known Implementing Classes:

Entropy, GiniIndex

public interface LabelImpurity
extends com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>

Calculates a tree impurity score based on label counts, weighted label counts or a probability distribution.

Method Summary

Modifier and Type	Method and Description
default double	impurity(double[] input) Calculates the impurity assuming the inputs are counts.
default double	impurity(float[] input) Calculates the impurity assuming the input are fractional counts.
default double	impurity(int[] input) Calculates the impurity assuming the input are counts.
default double	impurity(Map<String,Double> counts) Takes a Map for weighted counts.
double	impurityNormed(double[] input) Calculates the impurity, assuming it's input is a normalized probability distribution.
default double	impurityWeighted(double[] input) Calculates the impurity assuming the inputs are weighted counts normalizing by their sum.
default double	impurityWeighted(float[] input) Calculates the impurity by assuming the input are weighted counts and converting them into a probability distribution by dividing by their sum.

Methods inherited from interface com.oracle.labs.mlrg.olcut.config.Configurable

postConfig

Methods inherited from interface com.oracle.labs.mlrg.olcut.provenance.Provenancable

getProvenance

Method Detail

impurityNormed

double impurityNormed(double[] input)

Calculates the impurity, assuming it's input is a normalized probability distribution.

Parameters:

input - The input probability distribution.

Returns:

The impurity.

impurityWeighted

default double impurityWeighted(double[] input)

Calculates the impurity assuming the inputs are weighted counts normalizing by their sum.

Parameters:

input - The input counts.

Returns:

The impurity.

impurity

default double impurity(double[] input)

Calculates the impurity assuming the inputs are counts.

Parameters:

input - The input counts.

Returns:

The impurity.

impurityWeighted

default double impurityWeighted(float[] input)

Calculates the impurity by assuming the input are weighted counts and converting them into a probability distribution by dividing by their sum. The resulting impurity is then rescaled by multiplying by the sum.

Parameters:

input - The input counts.

Returns:

The impurity.

impurity

default double impurity(float[] input)

Calculates the impurity assuming the input are fractional counts.

Parameters:

input - The input counts.

Returns:

The impurity.

impurity

default double impurity(int[] input)

Calculates the impurity assuming the input are counts.

Parameters:

input - The input counts.

Returns:

The impurity.

impurity

default double impurity(Map<String,Double> counts)

Takes a Map for weighted counts. Normalizes into a probability distribution before calling impurityNormed(double[]).

Parameters:

counts - A map from instances to weighted counts.

Returns:

The impurity score.