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Carrot2 v3.5.2
API Documentation |
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java.lang.Objectorg.carrot2.clustering.lingo.UniqueLabelAssigner
public class UniqueLabelAssigner
Assigns unique labels to each base vector using a greedy algorithm. For each base
vector chooses the label that maximizes the base vector--label term vector cosine
similarity and has not been previously selected. Once a label is selected, it will not
be used to label any other vector. This algorithm does not create duplicate cluster
labels, which usually means that this assignment method will create more clusters than
SimpleLabelAssigner. This method is slightly slower than
SimpleLabelAssigner.
| Constructor Summary | |
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UniqueLabelAssigner()
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| Method Summary | |
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void |
assignLabels(LingoProcessingContext context,
org.apache.mahout.math.matrix.DoubleMatrix2D stemCos,
com.carrotsearch.hppc.IntIntOpenHashMap filteredRowToStemIndex,
org.apache.mahout.math.matrix.DoubleMatrix2D phraseCos)
Assigns labels to base vectors found by the matrix factorization. |
| Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
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public UniqueLabelAssigner()
| Method Detail |
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public void assignLabels(LingoProcessingContext context,
org.apache.mahout.math.matrix.DoubleMatrix2D stemCos,
com.carrotsearch.hppc.IntIntOpenHashMap filteredRowToStemIndex,
org.apache.mahout.math.matrix.DoubleMatrix2D phraseCos)
ILabelAssignerLingoProcessingContext.clusterLabelFeatureIndex and
LingoProcessingContext.clusterLabelScore arrays.
assignLabels in interface ILabelAssignercontext - contains all information about the current clustering requeststemCos - base vector -- single stems cosine matrixfilteredRowToStemIndex - mapping between row indices of stemCos and indices of
stems in PreprocessingContext.allStemsphraseCos - base vector -- phrase cosine matrix
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Please refer to project documentation at
http://project.carrot2.org |
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