smile.imputation

Class KMeansImputation

java.lang.Object

smile.imputation.KMeansImputation

All Implemented Interfaces:

MissingValueImputation

public class KMeansImputation
extends java.lang.Object
implements MissingValueImputation

Missing value imputation by K-Means clustering. First cluster data by K-Means with missing values and then impute missing values with the average value of each attribute in the clusters.

Constructor Summary

Constructors

Constructor and Description
KMeansImputation(int k) Constructor.
KMeansImputation(int k, int runs) Constructor.

Method Summary

Modifier and Type	Method and Description
void	impute(double[][] data) Impute missing values in the data.

Methods inherited from class java.lang.Object

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

Methods inherited from interface smile.imputation.MissingValueImputation

imputeWithColumnAverage

Constructor Detail

KMeansImputation

public KMeansImputation(int k)

Constructor.

Parameters:

k - the number of clusters in K-Means clustering.

KMeansImputation

public KMeansImputation(int k,
                        int runs)

Constructor.

Parameters:

k - the number of clusters in K-Means clustering.

runs - the number of runs of K-Means algorithm.

Method Detail

impute

public void impute(double[][] data)
            throws MissingValueImputationException

Description copied from interface: MissingValueImputation

Impute missing values in the data.

Specified by:

impute in interface MissingValueImputation

Parameters:

data - a data set with missing values (represented as Double.NaN). On output, missing values are filled with estimated values.

Throws:

MissingValueImputationException