1 write to LogLoss
Microsoft.ML.Data (1)
Evaluators\Metrics\CalibratedBinaryClassificationMetrics.cs (1)
68
LogLoss
= 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)
199
Assert.InRange(metrics.
LogLoss
, double.NegativeInfinity, 1);
Microsoft.ML.Predictor.Tests (1)
TestIniModels.cs (1)
595
Assert.Equal(0.11594021906091197, results.
LogLoss
);
Microsoft.ML.Samples (2)
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachine.cs (1)
206
Console.WriteLine($"Log Loss: {metrics.
LogLoss
:F2}");
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachineWithOptions.cs (1)
217
Console.WriteLine($"Log Loss: {metrics.
LogLoss
:F2}");
Microsoft.ML.Tests (9)
TrainerEstimators\SdcaTests.cs (3)
86
Assert.InRange(metrics.
LogLoss
, 0, 0.5);
133
Assert.Equal(0.3488, metrics1.
LogLoss
, 0.0001);
135
Assert.Equal(0.3591, metrics2.
LogLoss
, 0.0001);
TrainerEstimators\TrainerEstimators.cs (1)
112
Assert.InRange(metrics.
LogLoss
, 0, 0.6);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (5)
345
Assert.True(metrics.
LogLoss
< naiveMetrics.
LogLoss
);
384
Assert.True(metrics.
LogLoss
< 0.05);
423
Assert.True(metrics.
LogLoss
< 0.07);
758
Assert.True(metrics.
LogLoss
< 0.05);