Class KMeansStratiAssigner
- java.lang.Object
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- ai.libs.jaicore.ml.core.filter.sampling.inmemory.stratified.sampling.ClusterStratiAssigner
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- ai.libs.jaicore.ml.core.filter.sampling.inmemory.stratified.sampling.KMeansStratiAssigner
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- All Implemented Interfaces:
IStratiAssigner,org.api4.java.common.control.IParallelizable
public class KMeansStratiAssigner extends ClusterStratiAssigner
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.
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Field Summary
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Fields inherited from class ai.libs.jaicore.ml.core.filter.sampling.inmemory.stratified.sampling.ClusterStratiAssigner
distanceMeasure, randomSeed
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Constructor Summary
Constructors Constructor Description KMeansStratiAssigner(org.apache.commons.math3.ml.distance.DistanceMeasure distanceMeasure, int randomSeed)Constructor for KMeansStratiAssigner.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidinit(org.api4.java.ai.ml.core.dataset.IDataset<?> dataset, int stratiAmount)Initialize custom assigner if necessary.-
Methods inherited from class ai.libs.jaicore.ml.core.filter.sampling.inmemory.stratified.sampling.ClusterStratiAssigner
assignToStrati, getClusters, getNumCPUs, setClusters, setDataset, setNumCPUs
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Constructor Detail
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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.
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Method Detail
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init
public void init(org.api4.java.ai.ml.core.dataset.IDataset<?> dataset, int stratiAmount)Description copied from interface:IStratiAssignerInitialize 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.
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