DefaultTKSVMlightDataWriterFactory.java

/** 
 * Copyright (c) 2009, Regents of the University of Colorado 
 * All rights reserved.
 * 
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 
 * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 
 * Neither the name of the University of Colorado at Boulder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. 
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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package de.tudarmstadt.ukp.csniper.ml.tksvm;

import java.io.IOException;

import org.apache.uima.fit.descriptor.ConfigurationParameter;
import org.cleartk.classifier.DataWriter;
import org.cleartk.classifier.encoder.features.BooleanEncoder;
import org.cleartk.classifier.encoder.features.NumberEncoder;
import org.cleartk.classifier.encoder.features.StringEncoder;
import org.cleartk.classifier.encoder.features.normalizer.EuclidianNormalizer;
import org.cleartk.classifier.encoder.features.normalizer.NameNumberNormalizer;
import org.cleartk.classifier.encoder.outcome.BooleanToBooleanOutcomeEncoder;
import org.cleartk.classifier.jar.DataWriterFactory_ImplBase;
import org.cleartk.classifier.jar.DefaultDataWriterFactory;

/**
 * <br>
 * Copyright (c) 2009, Regents of the University of Colorado <br>
 * All rights reserved.
 * 
 * @author Daryl Lonnon
 * @version 0.2.1
 * 
 *          A Factory class for creating a tree kernel support vector model light data writer.
 * 
 *          It uses a TreeFeatureVector as it's feature vector which includes a SpareFeatureVector.
 *          In addition it uses the following encoders for it's non tree features: NumberEncoder,
 *          BooleanEncoder and StringEncoder. The default value for the cutoff is 5 (i.e. features
 *          that occur less than this number of times over the entire training set will not be
 *          encoded during testing). And it also uses a EuclideanNormalizer.
 * @deprecated Use {@link DefaultDataWriterFactory} with {@link TKSVMlightDataWriter}.
 */
@Deprecated
public class DefaultTKSVMlightDataWriterFactory extends
    DataWriterFactory_ImplBase<TreeFeatureVector, Boolean, Boolean> {

  public static final String PARAM_CUTOFF = "cutoff";

  @ConfigurationParameter(
      defaultValue = "5",
      description = "features that occur less than this number of times over the whole training set will not be encoded during testing")
  protected int cutoff = 5;

  /**
   * @return A DataWriter templatized over Boolean which writes out the format expected by the Tree
   *         Kernel SVM Light.
   */
  @Override
public DataWriter<Boolean> createDataWriter() throws IOException {
    TKSVMlightDataWriter dataWriter = new TKSVMlightDataWriter(outputDirectory);

    if (!this.setEncodersFromFileSystem(dataWriter)) {
      NameNumberNormalizer normalizer = new EuclidianNormalizer();
      TreeFeatureVectorFeaturesEncoder myFeaturesEncoder = new TreeFeatureVectorFeaturesEncoder(
          cutoff,
          normalizer);
      myFeaturesEncoder.addEncoder(new NumberEncoder());
      myFeaturesEncoder.addEncoder(new BooleanEncoder());
      myFeaturesEncoder.addEncoder(new StringEncoder());
      dataWriter.setFeaturesEncoder(myFeaturesEncoder);
      dataWriter.setOutcomeEncoder(new BooleanToBooleanOutcomeEncoder());
    }

    return dataWriter;
  }

}