RapidMiner

‎08-29-2017 06:55 PM

execute script-01.pngFast Large Margin is an SVM-Like algorithm which runs in O(n). This is very nice in terms of run time. It provides coefficient for each attribute which might be used as weights. To access them you need to use a small Groovy script in an Execute Script operator:

 

import com.rapidminer.operator.learner.functions.FastMarginModel;
import java.util.logging.Level;
import com.rapidminer.tools.Ontology;
import com.rapidminer.example.utils.ExampleSetBuilder;
import com.rapidminer.example.utils.ExampleSets;

FastMarginModel inputmodel = input[0];

ArrayList<Attribute> attributes = new ArrayList<Attribute>();
attributes.add(AttributeFactory.createAttribute("word", Ontology.NOMINAL));
attributes.add(AttributeFactory.createAttribute("weight", Ontology.REAL));

ExampleSetBuilder builder = ExampleSets.from(attributes);

for(int i = 0; i < inputmodel.attributeConstructions.length; ++i){
	double[] values = new double[2];
	values[0] = attributes.get(0).getMapping().mapString(inputmodel.attributeConstructions[i]);
	values[1] = inputmodel.linearModel.w[i]
	builder.addRow(values);
}
return builder.build()

Attached is a process demonstrating this.

 

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Head of Data Science Services at RapidMiner