2 writes to MeanSquaredError
Microsoft.ML.Data (2)
Evaluators\Metrics\RegressionMetrics.cs (2)
73
MeanSquaredError
= Fetch(RegressionEvaluator.L2);
83
MeanSquaredError
= l2;
60 references to MeanSquaredError
Microsoft.ML.AutoML (5)
API\RegressionExperiment.cs (2)
60
/// See <see cref="RegressionMetrics.
MeanSquaredError
"/>.
475
RegressionMetric.MeanSquaredError => metrics.
MeanSquaredError
,
AutoMLExperiment\IMetricManager.cs (1)
136
RegressionMetric.MeanSquaredError => metric.
MeanSquaredError
,
Experiment\MetricsAgents\RegressionMetricsAgent.cs (1)
32
return metrics.
MeanSquaredError
;
Experiment\Runners\CrossValSummaryRunner.cs (1)
139
l2: GetAverageOfNonNaNScores(newMetrics.Select(x => x.
MeanSquaredError
)),
Microsoft.ML.AutoML.Samples (2)
AutoFit\RecommendationExperiment.cs (1)
87
Console.WriteLine($"MeanSquaredError: {metrics.
MeanSquaredError
}");
AutoFit\RegressionExperiment.cs (1)
71
Console.WriteLine($"MeanSquaredError: {metrics.
MeanSquaredError
}");
Microsoft.ML.AutoML.Tests (1)
AutoFitTests.cs (1)
557
Assert.NotEqual(0, metrices.
MeanSquaredError
);
Microsoft.ML.Data (1)
Evaluators\Metrics\RegressionMetrics.cs (1)
49
/// Gets the root mean square loss (or RMS) which is the square root of the L2 loss <see cref="
MeanSquaredError
"/>.
Microsoft.ML.Fairlearn (2)
Metrics\FairlearnMetricCatalog.cs (2)
237
result["MSE"] = DataFrameColumn.Create("MSE", groupMetric.Keys.Select(k => groupMetric[k].
MeanSquaredError
));
263
{ "MSE", metrics.
MeanSquaredError
},
Microsoft.ML.IntegrationTests (1)
Common.cs (1)
273
Assert.True(metrics.
MeanSquaredError
>= 0);
Microsoft.ML.Predictor.Tests (1)
TestIniModels.cs (1)
549
Assert.Equal(0.025707474358979077, results.
MeanSquaredError
);
Microsoft.ML.Samples (24)
Dynamic\Trainers\Recommendation\MatrixFactorization.cs (1)
128
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Recommendation\MatrixFactorizationWithOptions.cs (1)
152
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastForest.cs (1)
111
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastForestWithOptions.cs (1)
124
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastTree.cs (1)
111
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastTreeTweedie.cs (1)
111
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastTreeTweedieWithOptions.cs (1)
126
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\FastTreeWithOptions.cs (1)
127
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\Gam.cs (1)
111
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\GamWithOptions.cs (1)
122
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LbfgsPoissonRegression.cs (1)
109
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LbfgsPoissonRegressionWithOptions.cs (1)
123
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LightGbm.cs (1)
112
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (1)
78
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LightGbmWithOptions.cs (1)
131
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (1)
87
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OnlineGradientDescent.cs (1)
100
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OnlineGradientDescentWithOptions.cs (1)
116
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OrdinaryLeastSquares.cs (1)
108
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresAdvanced.cs (1)
79
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptions.cs (1)
120
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptionsAdvanced.cs (1)
83
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\Sdca.cs (1)
108
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Dynamic\Trainers\Regression\SdcaWithOptions.cs (1)
124
Console.WriteLine("Mean Squared Error: " + metrics.
MeanSquaredError
);
Microsoft.ML.Tests (19)
TrainerEstimators\MatrixFactorizationTests.cs (7)
138
Assert.InRange(metrices.
MeanSquaredError
, expectedLinuxMeanSquaredError - linuxTolerance, expectedLinuxMeanSquaredError + linuxTolerance);
144
Assert.InRange(metrices.
MeanSquaredError
, expectedMacMeanSquaredError - windowsAndMacTolerance, expectedMacMeanSquaredError + windowsAndMacTolerance);
150
Assert.InRange(metrices.
MeanSquaredError
, expectedWindowsMeanSquaredError - windowsAndMacTolerance, expectedWindowsMeanSquaredError + windowsAndMacTolerance);
251
Assert.True(metrics.
MeanSquaredError
< 0.1);
362
Assert.InRange(metrics.
MeanSquaredError
, 0, 0.1);
475
Assert.InRange(metrics.
MeanSquaredError
, 0, 0.0016);
619
Assert.InRange(metrics.
MeanSquaredError
, 0, 0.0016);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (12)
462
Assert.True(metrics.
MeanSquaredError
< 0.05);
500
Assert.True(metrics.
MeanSquaredError
< 0.1);
538
Assert.True(metrics.
MeanSquaredError
< 0.1);
576
Assert.True(metrics.
MeanSquaredError
< 0.1);
614
Assert.True(metrics.
MeanSquaredError
< 0.1);
631
Assert.Equal(metrics.
MeanSquaredError
, loadedMetrics.
MeanSquaredError
, 0.00001);
671
Assert.True(metrics.
MeanSquaredError
< 0.1);
691
Assert.Equal(metrics.
MeanSquaredError
, loadedMetrics.
MeanSquaredError
, 0.00001);
705
Assert.NotEqual(metrics.
MeanSquaredError
, secondMetrics.
MeanSquaredError
);
Microsoft.ML.Transforms (4)
MetricStatistics.cs (2)
96
/// Summary statistics for <see cref="RegressionMetrics.
MeanSquaredError
"/>.
131
MeanSquaredError.Add(metrics.
MeanSquaredError
);
PermutationFeatureImportanceExtensions.cs (2)
166
l2: a.
MeanSquaredError
- b.
MeanSquaredError
,