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));
}
