1 write to LogLoss
Microsoft.ML.Data (1)
Evaluators\Metrics\CalibratedBinaryClassificationMetrics.cs (1)
68LogLoss = Fetch(BinaryClassifierEvaluator.LogLoss);
15 references to LogLoss
Microsoft.ML.Data (1)
Evaluators\Metrics\CalibratedBinaryClassificationMetrics.cs (1)
51/// and negative instances in the test set. A classifier's <see cref="LogLoss"/> lower than
Microsoft.ML.Fairlearn (1)
Metrics\FairlearnMetricCatalog.cs (1)
129{ "LogLoss", metrics.LogLoss },
Microsoft.ML.IntegrationTests (1)
Common.cs (1)
199Assert.InRange(metrics.LogLoss, double.NegativeInfinity, 1);
Microsoft.ML.Predictor.Tests (1)
TestIniModels.cs (1)
595Assert.Equal(0.11594021906091197, results.LogLoss);
Microsoft.ML.Samples (2)
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachine.cs (1)
206Console.WriteLine($"Log Loss: {metrics.LogLoss:F2}");
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachineWithOptions.cs (1)
217Console.WriteLine($"Log Loss: {metrics.LogLoss:F2}");
Microsoft.ML.Tests (9)
TrainerEstimators\SdcaTests.cs (3)
86Assert.InRange(metrics.LogLoss, 0, 0.5); 133Assert.Equal(0.3488, metrics1.LogLoss, 0.0001); 135Assert.Equal(0.3591, metrics2.LogLoss, 0.0001);
TrainerEstimators\TrainerEstimators.cs (1)
112Assert.InRange(metrics.LogLoss, 0, 0.6);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (5)
345Assert.True(metrics.LogLoss < naiveMetrics.LogLoss); 384Assert.True(metrics.LogLoss < 0.05); 423Assert.True(metrics.LogLoss < 0.07); 758Assert.True(metrics.LogLoss < 0.05);