public void MulticlassMetricsNonPerfectTest() { var metrics = MetricsUtil.CreateMulticlassClassificationMetrics(0.1, 0.2, 0.3, 0.4, 0, new double[] { 0.5 }, new double[] { }); Assert.False(IsPerfectModel(metrics, MulticlassClassificationMetric.MacroAccuracy)); Assert.False(IsPerfectModel(metrics, MulticlassClassificationMetric.MicroAccuracy)); Assert.False(IsPerfectModel(metrics, MulticlassClassificationMetric.LogLoss)); Assert.False(IsPerfectModel(metrics, MulticlassClassificationMetric.LogLossReduction)); Assert.False(IsPerfectModel(metrics, MulticlassClassificationMetric.TopKAccuracy)); }
public void MulticlassMetricsPerfectTest() { var metrics = MetricsUtil.CreateMulticlassClassificationMetrics(1, 1, 0, 1, 0, new double[] { 1 }, new double[] { }); Assert.True(IsPerfectModel(metrics, MulticlassClassificationMetric.MicroAccuracy)); Assert.True(IsPerfectModel(metrics, MulticlassClassificationMetric.MacroAccuracy)); Assert.True(IsPerfectModel(metrics, MulticlassClassificationMetric.LogLoss)); Assert.True(IsPerfectModel(metrics, MulticlassClassificationMetric.LogLossReduction)); Assert.True(IsPerfectModel(metrics, MulticlassClassificationMetric.TopKAccuracy)); }
public void MulticlassMetricsGetScoreTest() { var metrics = MetricsUtil.CreateMulticlassClassificationMetrics(0.1, 0.2, 0.3, 0.4, 0, new double[] { 0.5 }, new double[] { }); Assert.Equal(0.1, GetScore(metrics, MulticlassClassificationMetric.MicroAccuracy)); Assert.Equal(0.2, GetScore(metrics, MulticlassClassificationMetric.MacroAccuracy)); Assert.Equal(0.3, GetScore(metrics, MulticlassClassificationMetric.LogLoss)); Assert.Equal(0.4, GetScore(metrics, MulticlassClassificationMetric.LogLossReduction)); Assert.Equal(0.5, GetScore(metrics, MulticlassClassificationMetric.TopKAccuracy)); }