org.processmining.nlplogutils.algorithms.analysis.feature

Class HighDimClusteringProvider

java.lang.Object

org.processmining.nlplogutils.algorithms.analysis.feature.HighDimClusteringProvider

All Implemented Interfaces:

ContextFeatureProvider

Direct Known Subclasses:

HighDimClusteringSumOfVariancesProvider

public abstract class HighDimClusteringProvider
extends java.lang.Object
implements ContextFeatureProvider

Created by andreas on 2/22/17.

Field Summary

Fields

Modifier and Type	Field and Description
protected HighDimensionalContextCreator	contextProvider
protected org.apache.commons.math3.ml.clustering.evaluation.ClusterEvaluator<HighDimPoint>	evaluator
protected org.apache.commons.math3.ml.distance.DistanceMeasure	measure

Constructor Summary

Constructors

Constructor and Description
HighDimClusteringProvider()

Method Summary

Modifier and Type	Method and Description
double[]	computeFeature(org.apache.commons.collections4.MultiSet<Context> equalContexts) Extracts a feature from the context.
protected abstract org.apache.commons.math3.ml.clustering.evaluation.ClusterEvaluator<HighDimPoint>	getClusterEvaluator(org.apache.commons.math3.ml.distance.DistanceMeasure measure) Gets the evaluator that will compute the score based on the clustering available for this method.
int	getNumberOfResultFeatures() If a feature provider computes 1 feature, it return 1, if 2, then 2.

Methods inherited from class java.lang.Object

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

Field Detail

contextProvider

protected final HighDimensionalContextCreator contextProvider

measure

protected final org.apache.commons.math3.ml.distance.DistanceMeasure measure

evaluator

protected final org.apache.commons.math3.ml.clustering.evaluation.ClusterEvaluator<HighDimPoint> evaluator

Constructor Detail

HighDimClusteringProvider

public HighDimClusteringProvider()

Method Detail

getClusterEvaluator

protected abstract org.apache.commons.math3.ml.clustering.evaluation.ClusterEvaluator<HighDimPoint> getClusterEvaluator(org.apache.commons.math3.ml.distance.DistanceMeasure measure)

Gets the evaluator that will compute the score based on the clustering available for this method.

Parameters:

measure - the DistanceMeasure used in the clusters

Returns:

an evaluator of type ClusterEvaluator

computeFeature

public final double[] computeFeature(org.apache.commons.collections4.MultiSet<Context> equalContexts)

Description copied from interface: ContextFeatureProvider

Extracts a feature from the context. A context is an int[] where individual event classes are encoded as integers. A typical context of an event would be a symmetric window of size 4. Let us consider the trace (with event ids in brackets): a(1), b(2), c(3), b(2), d(4), e(5) A symmetric window context of event c in this trace would be: {1,2,2,4} b has two occurrences. Therefore, it has two contexts: {-1,1,3,2}, and {2,3,4,5}. Contexts can be defined left, right, or symmetric. See ContextParameters.WindowType

Specified by:

computeFeature in interface ContextFeatureProvider

Parameters:

equalContexts - a preprocessed bag/multiset of contexts

Returns:

some feature of this context depending on the subclass.

getNumberOfResultFeatures

public int getNumberOfResultFeatures()

Description copied from interface: ContextFeatureProvider

If a feature provider computes 1 feature, it return 1, if 2, then 2. :) This is useful, as some feature providers need to to complex computation and can provide a number of results based on that See for example the HighDimClusteringProvider that returns the number of clusters and a cluster variance metric.

Specified by:

getNumberOfResultFeatures in interface ContextFeatureProvider

Returns: