Class KModes

java.lang.Object

smile.clustering.KModes

public class KModes
extends Object

K-Modes clustering. K-Modes is the binary equivalent for K-Means. The mean update for centroids is replaced by the mode one which is a majority vote among element of each cluster.

References

1. Joshua Zhexue Huang. Clustering Categorical Data with k-Modes.

See Also:

• KMeans

Method Summary

Modifier and Type	Method	Description
static CentroidClustering<int[],int[]>	fit(int[][] data, int k, int maxIter)	Fits k-modes clustering.
static CentroidClustering<int[],int[]>	fit(int[][] data, Clustering.Options options)	Fits k-modes clustering.

Methods inherited from class Object

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

Method Details

fit

public static CentroidClustering<int[],int[]> fit(int[][] data,
 int k,
 int maxIter)

Fits k-modes clustering.

Parameters:

data - the input data of which each row is an observation.

k - the number of clusters.

maxIter - the maximum number of iterations.

Returns:

the model.

fit

public static CentroidClustering<int[],int[]> fit(int[][] data,
 Clustering.Options options)

Fits k-modes clustering.

Parameters:

data - the input data of which each row is an observation.

options - the hyperparameters.

Returns:

the model.