public void BinaryMetricsNonPerfectTest() { var metrics = MetricsUtil.CreateBinaryClassificationMetrics(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.Accuracy)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.AreaUnderRocCurve)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.AreaUnderPrecisionRecallCurve)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.F1Score)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.NegativePrecision)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.NegativeRecall)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.PositivePrecision)); Assert.False(IsPerfectModel(metrics, BinaryClassificationMetric.PositiveRecall)); }
public void BinaryMetricsPerfectTest() { var metrics = MetricsUtil.CreateBinaryClassificationMetrics(1, 1, 1, 1, 1, 1, 1, 1); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.Accuracy)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.AreaUnderRocCurve)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.AreaUnderPrecisionRecallCurve)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.F1Score)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.NegativePrecision)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.NegativeRecall)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.PositivePrecision)); Assert.True(IsPerfectModel(metrics, BinaryClassificationMetric.PositiveRecall)); }
public void BinaryMetricsGetScoreTest() { var metrics = MetricsUtil.CreateBinaryClassificationMetrics(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8); Assert.Equal(0.1, GetScore(metrics, BinaryClassificationMetric.AreaUnderRocCurve)); Assert.Equal(0.2, GetScore(metrics, BinaryClassificationMetric.Accuracy)); Assert.Equal(0.3, GetScore(metrics, BinaryClassificationMetric.PositivePrecision)); Assert.Equal(0.4, GetScore(metrics, BinaryClassificationMetric.PositiveRecall)); Assert.Equal(0.5, GetScore(metrics, BinaryClassificationMetric.NegativePrecision)); Assert.Equal(0.6, GetScore(metrics, BinaryClassificationMetric.NegativeRecall)); Assert.Equal(0.7, GetScore(metrics, BinaryClassificationMetric.F1Score)); Assert.Equal(0.8, GetScore(metrics, BinaryClassificationMetric.AreaUnderPrecisionRecallCurve)); }