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I tried to run COPAC ELKI implementation on the example dataset provided on the official site (mouse.csv) but I get a NullPointerException which leads me to think that there is some detail that I omit (shame on me).

The exception is the following:

Task failed java.lang.NullPointerException at de.lmu.ifi.dbs.elki.database.ids.integer.DoubleDistanceIntegerDBIDPair.compareByDistance(Unknown Source) at de.lmu.ifi.dbs.elki.distance.distanceresultlist.AbstractKNNHeap$Comp.compare(Unknown Source) at de.lmu.ifi.dbs.elki.distance.distanceresultlist.AbstractKNNHeap$Comp.compare(Unknown Source) at de.lmu.ifi.dbs.elki.utilities.datastructures.heap.TopBoundedHeap.add(Unknown Source) at de.lmu.ifi.dbs.elki.database.query.knn.LinearScanRawDoubleDistanceKNNQuery.getKNNForObjectBenchmarked(Unknown Source) at de.lmu.ifi.dbs.elki.database.query.knn.LinearScanRawDoubleDistanceKNNQuery.getKNNForObject(Unknown Source) at de.lmu.ifi.dbs.elki.database.query.knn.LinearScanRawDoubleDistanceKNNQuery.getKNNForDBID(Unknown Source) at de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.objectsForPCA(Unknown Source) at de.lmu.ifi.dbs.elki.index.preprocessed.localpca.KNNQueryFilteredPCAIndex.objectsForPCA(Unknown Source) at de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex.preprocess(Unknown Source) at de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex.getLocalProjection(Unknown Source) at de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex.getLocalProjection(Unknown Source) at de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC.run(Unknown Source) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:616) at de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm.run(Unknown Source) at de.lmu.ifi.dbs.elki.workflow.AlgorithmStep.runAlgorithms(Unknown Source) at [...]

This is the setting of the parameters that I use:

-dbc.in [PATH OMITTED]/mouse.csv

-algorithm clustering.correlation.COPAC

-copac.preprocessor localpca.KNNQueryFilteredPCAIndex

-copac.partitionAlgorithm gdbscan.GeneralizedDBSCAN

-dbscan.epsilon 0.00400000

-dbscan.minpts 3

Can anyone give me some info?

Gibbster
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1 Answers1

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You must specify the k parameter for kNN Local PCA:

-localpca.k 10

there is a slight bug in the last ELKI release, where the parameter is incorrectly marked as optional. It is not optional. Note that k should be significantly larger than the data dimensionality to give stable PCA results.

Note that using COPAC on a low dimensional data set such as the mouse example does not make sense.

Erich Schubert
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  • I discovered it this morning! I ran it on the example of the mouse after trying it on my dataset ... just trying to understand why it did not work. Anyway thanks for the answer, you have been very kind and helpful! – Gibbster Mar 13 '13 at 09:07