Examples with Feature edu.cmu.minorthird.classify.Feature used on opensource projects

Example 6 with Feature

use of edu.cmu.minorthird.classify.Feature in project lucida by claritylab.

the class ScoreNormalizationFilter method addMaxScoreFeature.

/**
	 * Adds the maximum score of all factoid answers from the same extractor as
	 * a feature to the instance.
	 */
private static void addMaxScoreFeature(MutableInstance instance, Result result, Result[] results) {
    // calculate maximum score
    double maxScore = 0;
    //		String extractor = result.getExtractionTechniques()[0];
    for (Result r : results) if (r.getScore() > 0 && r.getScore() < Float.POSITIVE_INFINITY)
        //				if (r.extractedWith(extractor))
        maxScore = Math.max(r.getScore(), maxScore);
    Feature feature = new Feature(MAX_SCORE_F);
    instance.addNumeric(feature, maxScore);
}

Example 7 with Feature

use of edu.cmu.minorthird.classify.Feature in project lucida by claritylab.

the class ScoreNormalizationFilter method addScoreFeature.

/**
	 * Adds the score of the answer candidate as a feature to the instance.
	 */
private static void addScoreFeature(MutableInstance instance, Result result) {
    float score = result.getScore();
    Feature feature = new Feature(SCORE_F);
    instance.addNumeric(feature, score);
}

Example 8 with Feature

use of edu.cmu.minorthird.classify.Feature in project lucida by claritylab.

the class ScoreNormalizationFilter method addMeanScoreFeature.

/**
	 * Adds the mean score of all factoid answers from the same extractor as a
	 * feature to the instance.
	 */
private static void addMeanScoreFeature(MutableInstance instance, Result result, Result[] results) {
    // calculate mean score
    double meanScore = 0;
    int numFactoid = 0;
    //		String extractor = result.getExtractionTechniques()[0];
    for (Result r : results) if (r.getScore() > 0 && r.getScore() < Float.POSITIVE_INFINITY) {
        //				if (r.extractedWith(extractor)) {
        meanScore += r.getScore();
        numFactoid++;
    //				}
    }
    meanScore /= numFactoid;
    Feature feature = new Feature(MEAN_SCORE_F);
    instance.addNumeric(feature, meanScore);
}

Example 9 with Feature

use of edu.cmu.minorthird.classify.Feature in project lucida by claritylab.

the class ScoreNormalizationFilter method addNumAnswersFeature.

/**
	 * Adds the number of factoid answers from the same extractor as a feature
	 * to the instance.
	 */
private static void addNumAnswersFeature(MutableInstance instance, Result result, Result[] results) {
    // get number of factoid answers
    int numFactoid = 0;
    //		String extractor = result.getExtractionTechniques()[0];
    for (Result r : results) if (r.getScore() > 0 && r.getScore() < Float.POSITIVE_INFINITY)
        //				if (r.extractedWith(extractor))
        numFactoid++;
    Feature feature = new Feature(NUM_ANSWERS_F);
    instance.addNumeric(feature, numFactoid);
}

Example 10 with Feature

use of edu.cmu.minorthird.classify.Feature in project lucida by claritylab.

the class ScoreNormalizationFilter method addExtractorFeature.

/**
	 * Adds the extractor used to obtain the answer candidate as a feature to
	 * the instance.
	 */
private static void addExtractorFeature(MutableInstance instance, Result result) {
    String extractor = result.getExtractionTechniques()[0];
    Feature feature = new Feature(extractor);
    instance.addBinary(feature);
}