options.add(getEvaluationMetric().getSelectedTag().getIDStr()); if (getClassValueIndex() >= 0) { options.add("-class-value-index"); options.add("" + getClassValueIndex());
options.add(getEvaluationMetric().getSelectedTag().getIDStr()); if (getClassValueIndex() >= 0) { options.add("-class-value-index"); options.add("" + getClassValueIndex());
getClassValueIndex() >= 0 ? helper.getNamedMetric(m_evalMetric, getClassValueIndex()) : helper.getNamedMetric(m_evalMetric); tempThresholds = helper.getNamedMetricThresholds(m_evalMetric); } else { eval.evaluateModel(classifiers[r][i], testSets[r][i]); result += getClassValueIndex() >= 0 ? helper.getNamedMetric(m_evalMetric, getClassValueIndex()) : helper.getNamedMetric(m_evalMetric); double[] thresholds = helper.getNamedMetricThresholds(m_evalMetric);
getClassValueIndex() >= 0 ? helper.getNamedMetric(m_evalMetric, getClassValueIndex()) : helper.getNamedMetric(m_evalMetric); tempThresholds = helper.getNamedMetricThresholds(m_evalMetric); } else { eval.evaluateModel(classifiers[r][i], testSets[r][i]); result += getClassValueIndex() >= 0 ? helper.getNamedMetric(m_evalMetric, getClassValueIndex()) : helper.getNamedMetric(m_evalMetric); double[] thresholds = helper.getNamedMetricThresholds(m_evalMetric);