Example usage for org.apache.mahout.cf.taste.eval IRStatistics getFallOut

Introduction

In this page you can find the example usage for org.apache.mahout.cf.taste.eval IRStatistics getFallOut.

Prototype

double getFallOut();

Source Link

Document

<p> See <a href="http://en.wikipedia.org/wiki/Information_retrieval#Fall-Out">Fall-Out</a>.

Usage

From source file:nl.gridline.zieook.client.tools.ZieOokEvaluatorTest.java

License:Apache License

@Test
public void evaluate5() {
    // RecommenderIRStatsEvaluator
    // ItemBasedRecommenderBuilder
    // TanimotoCoefficientSimilarity

    // IRStatistics stats =
    // evaluator.evaluate(builder, myModel, null, 3,
    // RecommenderIRStatusEvaluator.CHOOSE_THRESHOLD,
    // §1.0);

    try {//from w ww.  ja  v  a  2 s  .c  o m
        DataModel model = createDataBooleanModel(input);

        RecommenderIRStatsEvaluator evaluator = new GenericRecommenderIRStatsEvaluator();
        IRStatistics evaluation = evaluator.evaluate(
                new ItemBasedRecommenderBuilder(TanimotoCoefficientSimilarity.class.getCanonicalName()),
                new BooleanDataModelBuilder(), model, null, 3,
                GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD, 0.9);
        LOG.info("result: " + evaluation);

        writetofile("ItemBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-F1,"
                + evaluation.getF1Measure() + "\n");
        // getFNMeasure
        // writetofile("ItemBasedRecommenderBuilder,EuclideanDistanceSimilarity,RecommenderIRStatsEvaluator-F1,"
        // + evaluation.getFNMeasure(n) + "\n");
        writetofile(
                "ItemBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-FallOut,"
                        + evaluation.getFallOut() + "\n");
        writetofile(
                "ItemBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-precision,"
                        + evaluation.getPrecision() + "\n");
        writetofile(
                "ItemBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-recall,"
                        + evaluation.getRecall() + "\n");

        evaluator = new GenericRecommenderIRStatsEvaluator();
        evaluation = evaluator.evaluate(
                new UserBasedRecommenderBuilder(TanimotoCoefficientSimilarity.class.getCanonicalName()),
                new BooleanDataModelBuilder(), model, null, 3, 3, 0.9);
        LOG.info("result: " + evaluation);

        writetofile("UserBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-F1,"
                + evaluation.getF1Measure() + "\n");
        // getFNMeasure
        // writetofile("ItemBasedRecommenderBuilder,EuclideanDistanceSimilarity,RecommenderIRStatsEvaluator-F1,"
        // + evaluation.getFNMeasure(n) + "\n");
        writetofile(
                "UserBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-FallOut,"
                        + evaluation.getFallOut() + "\n");
        writetofile(
                "UserBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-precision,"
                        + evaluation.getPrecision() + "\n");
        writetofile(
                "UserBasedRecommenderBuilder,TanimotoCoefficientSimilarity,RecommenderIRStatsEvaluator-recall,"
                        + evaluation.getRecall() + "\n");

    } catch (TasteException e) {
        LOG.error("faild evaulate", e);
        fail();
    }

}

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