public void incrementCount(String correctLabel, String classifiedLabel, int count) { putCount(correctLabel, classifiedLabel, count + getCount(correctLabel, classifiedLabel)); }
public void incrementCount(String correctLabel, String classifiedLabel, int count) { putCount(correctLabel, classifiedLabel, count + getCount(correctLabel, classifiedLabel)); }
public void incrementCount(String correctLabel, String classifiedLabel, int count) { putCount(correctLabel, classifiedLabel, count + getCount(correctLabel, classifiedLabel)); }
private static ConfusionMatrix fillConfusionMatrix(int[][] values, String[] labels, String defaultLabel) { Collection<String> labelList = Lists.newArrayList(); labelList.add(labels[0]); labelList.add(labels[1]); ConfusionMatrix confusionMatrix = new ConfusionMatrix(labelList, defaultLabel); confusionMatrix.putCount("Label1", "Label1", values[0][0]); confusionMatrix.putCount("Label1", "Label2", values[0][1]); confusionMatrix.putCount("Label2", "Label1", values[1][0]); confusionMatrix.putCount("Label2", "Label2", values[1][1]); confusionMatrix.putCount("Label1", DEFAULT_LABEL, OTHER[0]); confusionMatrix.putCount("Label2", DEFAULT_LABEL, OTHER[1]); return confusionMatrix; }
/** * Example taken from * http://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_fscore_support.html */ @Test public void testPrecisionRecallAndF1ScoreAsScikitLearn() { Collection<String> labelList = Arrays.asList("0", "1", "2"); ConfusionMatrix confusionMatrix = new ConfusionMatrix(labelList, "DEFAULT"); confusionMatrix.putCount("0", "0", 2); confusionMatrix.putCount("1", "0", 1); confusionMatrix.putCount("1", "2", 1); confusionMatrix.putCount("2", "1", 2); double delta = 0.001; assertEquals(0.222, confusionMatrix.getWeightedPrecision(), delta); assertEquals(0.333, confusionMatrix.getWeightedRecall(), delta); assertEquals(0.266, confusionMatrix.getWeightedF1score(), delta); }