📄 realvaluemodeltests.java
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package opennlp.maxent;
import java.io.IOException;
import junit.framework.TestCase;
public class RealValueModelTests extends TestCase {
public void testRealValuedWeightsVsRepeatWeighting() throws IOException {
RealValueFileEventStream rvfes1 = new RealValueFileEventStream("test/data/opennlp/maxent/real-valued-weights-training-data.txt");
GISModel realModel = GIS.trainModel(100,new OnePassRealValueDataIndexer(rvfes1,1));
FileEventStream rvfes2 = new FileEventStream("test/data/opennlp/maxent/repeat-weighting-training-data.txt");
GISModel repeatModel = GIS.trainModel(100,new OnePassRealValueDataIndexer(rvfes2,1));
String[] features2Classify = new String[] {"feature2","feature5"};
double[] realResults = realModel.eval(features2Classify);
double[] repeatResults = repeatModel.eval(features2Classify);
assertEquals(realResults.length, repeatResults.length);
for(int i=0; i<realResults.length; i++) {
assertEquals(realResults[i], repeatResults[i], 0.01f);
System.out.println(String.format("classifiy with realModel: %1$s = %2$f", realModel.getOutcome(i), realResults[i]));
System.out.println(String.format("classifiy with repeatModel: %1$s = %2$f", repeatModel.getOutcome(i), repeatResults[i]));
}
features2Classify = new String[] {"feature1","feature2","feature3","feature4","feature5"};
realResults = realModel.eval(features2Classify, new float[] {5.5f, 6.1f, 9.1f, 4.0f, 1.8f});
repeatResults = repeatModel.eval(features2Classify, new float[] {5.5f, 6.1f, 9.1f, 4.0f, 1.8f});
System.out.println();
assertEquals(realResults.length, repeatResults.length);
for(int i=0; i<realResults.length; i++) {
assertEquals(realResults[i], repeatResults[i], 0.01f);
System.out.println(String.format("classifiy with realModel: %1$s = %2$f", realModel.getOutcome(i), realResults[i]));
System.out.println(String.format("classifiy with repeatModel: %1$s = %2$f", repeatModel.getOutcome(i), repeatResults[i]));
}
}
}
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