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P

Parameterizer() - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering1.Parameterizer
 
Parameterizer() - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering2.Parameterizer
 
Parameterizer() - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3.Parameterizer
 
Parameterizer() - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4.Parameterizer
 
Parameterizer() - Constructor for class tutorial.clustering.SameSizeKMeansAlgorithm.Parameterizer
 
Parameterizer() - Constructor for class tutorial.distancefunction.MultiLPNorm.Parameterizer
 
Parameterizer() - Constructor for class tutorial.outlier.DistanceStddevOutlier.Parameterizer
 
Parameterizer() - Constructor for class tutorial.outlier.ODIN.Parameterizer
 
PassingDataToELKI - Class in tutorial.javaapi
Example program to generate a random data set, and run k-means on it.
PassingDataToELKI() - Constructor for class tutorial.javaapi.PassingDataToELKI
 
pinv - Variable in class tutorial.distancefunction.MultiLPNorm
Normalization factor (count(ps)/sum(ps))
PreferenceComparator() - Constructor for class tutorial.clustering.SameSizeKMeansAlgorithm.PreferenceComparator
 
primary - Variable in class tutorial.clustering.SameSizeKMeansAlgorithm.Meta
Indexes: primary assignment (current or best), secondary assignment (second best or worst).
priority() - Method in class tutorial.clustering.SameSizeKMeansAlgorithm.Meta
Priority / badness: difference between best and worst.
processNewResult(ResultHierarchy, Result) - Method in class tutorial.outlier.SimpleScoreDumper
 
ps - Variable in class tutorial.distancefunction.MultiLPNorm.Parameterizer
P exponents
ps - Variable in class tutorial.distancefunction.MultiLPNorm
The exponents
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ELKI Version 0.7.1

Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.