Package org.apache.mahout.classifier.df.data

Examples of org.apache.mahout.classifier.df.data.Dataset.labels()


        if (dataset.isNumerical(dataset.getLabelId())) {
          RegressionResultAnalyzer regressionAnalyzer = new RegressionResultAnalyzer();
          regressionAnalyzer.setInstances(results);
          log.info("{}", regressionAnalyzer);
        } else {
          ResultAnalyzer analyzer = new ResultAnalyzer(Arrays.asList(dataset.labels()), "unknown");
          for (double[] res : results) {
            analyzer.addInstance(dataset.getLabelString(res[0]),
              new ClassifierResult(dataset.getLabelString(res[1]), 1.0));
          }
          log.info("{}", analyzer);
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        RegressionResultAnalyzer regressionAnalyzer = new RegressionResultAnalyzer();
        double[][] results = new double[resList.size()][2];
        regressionAnalyzer.setInstances(resList.toArray(results));
        log.info("{}", regressionAnalyzer);
      } else {
        ResultAnalyzer analyzer = new ResultAnalyzer(Arrays.asList(dataset.labels()), "unknown");
        for (double[] r : resList) {
          analyzer.addInstance(dataset.getLabelString(r[0]),
            new ClassifierResult(dataset.getLabelString(r[1]), 1.0));
        }
        log.info("{}", analyzer);
View Full Code Here

        if (dataset.isNumerical(dataset.getLabelId())) {
          RegressionResultAnalyzer regressionAnalyzer = new RegressionResultAnalyzer();
          regressionAnalyzer.setInstances(results);
          log.info("{}", regressionAnalyzer);
        } else {
          ResultAnalyzer analyzer = new ResultAnalyzer(Arrays.asList(dataset.labels()), "unknown");
          for (double[] res : results) {
            analyzer.addInstance(dataset.getLabelString(res[0]),
              new ClassifierResult(dataset.getLabelString(res[1]), 1.0));
          }
          log.info("{}", analyzer);
View Full Code Here

        RegressionResultAnalyzer regressionAnalyzer = new RegressionResultAnalyzer();
        double[][] results = new double[resList.size()][2];
        regressionAnalyzer.setInstances(resList.toArray(results));
        log.info("{}", regressionAnalyzer);
      } else {
        ResultAnalyzer analyzer = new ResultAnalyzer(Arrays.asList(dataset.labels()), "unknown");
        for (double[] r : resList) {
          analyzer.addInstance(dataset.getLabelString(r[0]),
            new ClassifierResult(dataset.getLabelString(r[1]), 1.0));
        }
        log.info("{}", analyzer);
View Full Code Here

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