ai.libs.jaicore.ml.core.dataset.sampling.inmemory.stratified.sampling

Class KMeansStratiAssigner<I extends INumericArrayInstance,D extends IDataset<I>>

java.lang.Object

ai.libs.jaicore.ml.core.dataset.sampling.inmemory.stratified.sampling.ClusterStratiAssigner<I,D>

ai.libs.jaicore.ml.core.dataset.sampling.inmemory.stratified.sampling.KMeansStratiAssigner<I,D>

All Implemented Interfaces:

IStratiAssigner<I,D>

public class KMeansStratiAssigner<I extends INumericArrayInstance,D extends IDataset<I>>
extends ClusterStratiAssigner<I,D>

Cluster the data set with k-means into k Clusters, where each cluster stands for one stratum. The datapoint assignment is performed with a lookup in the clusters.

Field Summary

Fields inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.stratified.sampling.ClusterStratiAssigner

clusters, distanceMeasure, randomSeed

Constructor Summary

Constructors

Constructor and Description
KMeansStratiAssigner(org.apache.commons.math3.ml.distance.DistanceMeasure distanceMeasure, int randomSeed) Constructor for KMeansStratiAssigner.

Method Summary

Modifier and Type	Method and Description
void	init(D dataset, int stratiAmount) Initialize custom assigner if necessary.

Methods inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.stratified.sampling.ClusterStratiAssigner

assignToStrati, getNumCPUs, setNumCPUs

Methods inherited from class java.lang.Object

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

Constructor Detail

KMeansStratiAssigner

public KMeansStratiAssigner(org.apache.commons.math3.ml.distance.DistanceMeasure distanceMeasure,
                            int randomSeed)

Constructor for KMeansStratiAssigner.

Parameters:

distanceMeasure - Distance measure for datapoints, for example Manhattan or Euclidian.

randomSeed - Seed for random numbers.

Method Detail

init

public void init(D dataset,
                 int stratiAmount)

Description copied from interface: IStratiAssigner

Initialize custom assigner if necessary.

Parameters:

dataset - The dataset the datapoints will be sampled from.

stratiAmount - The predetermined amount of strati the dataset will be stratified into.