Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter. Like the clusterer, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.
Valid options are:
-F <filter specification> Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2" (default: weka.filters.AllFilter)
-W Full name of base clusterer. (default: weka.clusterers.SimpleKMeans)
Options specific to clusterer weka.clusterers.SimpleKMeans:
-N <num> number of clusters. (default 2).
-V Display std. deviations for centroids.
-M Replace missing values with mean/mode.
-S <num> Random number seed. (default 10)
Based on code from the FilteredClassifier by Len Trigg.
@author Len Trigg (trigg@cs.waikato.ac.nz)
@author FracPete (fracpete at waikato dot ac dot nz)
@version $Revision: 5538 $
@see weka.classifiers.meta.FilteredClassifier