Examples of weka.attributeSelection.GreedyStepwise

weka.attributeSelection.GreedyStepwise

GreedyStepwise :

Performs a greedy forward or backward search through the space of attribute subsets. May start with no/all attributes or from an arbitrary point in the space. Stops when the addition/deletion of any remaining attributes results in a decrease in evaluation. Can also produce a ranked list of attributes by traversing the space from one side to the other and recording the order that attributes are selected.

Valid options are:

 -C Use conservative forward search

 -B Use a backward search instead of a forward one.

 -P <start set> Specify a starting set of attributes. Eg. 1,3,5-7.

 -R Produce a ranked list of attributes.

 -T <threshold> Specify a theshold by which attributes may be discarded from the ranking. Use in conjuction with -R

 -N <num to select> Specify number of attributes to select

@author Mark Hall @version $Revision: 7267 $

    public void addAttSelFilter(gui_WekaExperiment de) {
        try {


            AttributeSelection attSel = new AttributeSelection();
            CfsSubsetEval eval = new CfsSubsetEval();
            GreedyStepwise search = new GreedyStepwise();
            attSel.setEvaluator(eval);
            attSel.setSearch(search);
            //weka.filters.supervised.attribute.AttributeSelection -E "weka.attributeSelection.CfsSubsetEval " -S "weka.attributeSelection.BestFirst -D 1 -N 5"
            //String[] opt = {"-E", "\"weka.attributeSelection.CfsSubsetEval \"","-s","\"weka.attributeSelection.BestFirst -D 1 -N 5\"" };
            de.addFilter("weka.filters.supervised.attribute.AttributeSelection", attSel.getOptions());

Related Classes of weka.attributeSelection.GreedyStepwise

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