smile.classification

Class ClassLabels

java.lang.Object

smile.classification.ClassLabels

All Implemented Interfaces:

java.io.Serializable

public class ClassLabels
extends java.lang.Object
implements java.io.Serializable

Map arbitrary class labels to [0, k), where k is the number of classes.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
int	k The number of classes.
smile.util.IntSet	labels The class labels.
int[]	ni The number of samples per classes.
double[]	priori The estimated priori probabilities.
int[]	y The sample class id in [0, k).

Constructor Summary

Constructors

Constructor and Description
ClassLabels(int k, int[] y, smile.util.IntSet labels) Constructor.

Method Summary

Modifier and Type	Method and Description
static ClassLabels	fit(smile.data.vector.BaseVector response) Learns the class label mapping from samples.
static ClassLabels	fit(int[] y) Learns the class label mapping from samples.
int[]	indexOf(int[] y) Maps the class labels to index.
smile.data.measure.NominalScale	scale() Returns the nominal scale for the class labels.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

k

public final int k

The number of classes.

labels

public final smile.util.IntSet labels

The class labels. If the class labels are already in [0, k), this is empty.

y

public final int[] y

The sample class id in [0, k).

ni

public final int[] ni

The number of samples per classes.

priori

public final double[] priori

The estimated priori probabilities.

Constructor Detail

ClassLabels

public ClassLabels(int k,
                   int[] y,
                   smile.util.IntSet labels)

Constructor.

Method Detail

scale

public smile.data.measure.NominalScale scale()

Returns the nominal scale for the class labels.

indexOf

public int[] indexOf(int[] y)

Maps the class labels to index.

fit

public static ClassLabels fit(int[] y)

Learns the class label mapping from samples.

fit

public static ClassLabels fit(smile.data.vector.BaseVector response)

Learns the class label mapping from samples.