1 instantiation of RegressionMetrics
Microsoft.ML.Data (1)
Evaluators\RegressionEvaluator.cs (1)
192result = new RegressionMetrics(Host, cursor);
191 references to RegressionMetrics
Microsoft.ML.AutoML (53)
API\RecommendationExperiment.cs (5)
56public sealed class RecommendationExperiment : ExperimentBase<RegressionMetrics, RecommendationExperimentSettings> 68private protected override CrossValidationRunDetail<RegressionMetrics> GetBestCrossValRun(IEnumerable<CrossValidationRunDetail<RegressionMetrics>> results) 73private protected override RunDetail<RegressionMetrics> GetBestRun(IEnumerable<RunDetail<RegressionMetrics>> results)
API\RegressionExperiment.cs (38)
55/// See <see cref="RegressionMetrics.MeanAbsoluteError"/>. 60/// See <see cref="RegressionMetrics.MeanSquaredError"/>. 65/// See <see cref="RegressionMetrics.RootMeanSquaredError"/>. 70/// See <see cref="RegressionMetrics.RSquared"/>. 120public sealed class RegressionExperiment : ExperimentBase<RegressionMetrics, RegressionExperimentSettings> 145public override ExperimentResult<RegressionMetrics> Execute(IDataView trainData, ColumnInformation columnInformation, IEstimator<ITransformer> preFeaturizer = null, IProgress<RunDetail<RegressionMetrics>> progressHandler = null) 163TrialResultMonitor<RegressionMetrics> monitor = null; 168monitor = new TrialResultMonitor<RegressionMetrics>(channel, pipeline); 183var result = new ExperimentResult<RegressionMetrics>(runDetails, bestRun); 194public override ExperimentResult<RegressionMetrics> Execute(IDataView trainData, IDataView validationData, ColumnInformation columnInformation, IEstimator<ITransformer> preFeaturizer = null, IProgress<RunDetail<RegressionMetrics>> progressHandler = null) 204TrialResultMonitor<RegressionMetrics> monitor = null; 209monitor = new TrialResultMonitor<RegressionMetrics>(channel, pipeline); 224var result = new ExperimentResult<RegressionMetrics>(runDetails, bestRun); 229public override ExperimentResult<RegressionMetrics> Execute(IDataView trainData, IDataView validationData, string labelColumnName = "Label", IEstimator<ITransformer> preFeaturizer = null, IProgress<RunDetail<RegressionMetrics>> progressHandler = null) 239public override ExperimentResult<RegressionMetrics> Execute(IDataView trainData, string labelColumnName = "Label", string samplingKeyColumn = null, IEstimator<ITransformer> preFeaturizer = null, IProgress<RunDetail<RegressionMetrics>> progressHandler = null) 250public override CrossValidationExperimentResult<RegressionMetrics> Execute(IDataView trainData, uint numberOfCVFolds, ColumnInformation columnInformation = null, IEstimator<ITransformer> preFeaturizer = null, IProgress<CrossValidationRunDetail<RegressionMetrics>> progressHandler = null) 260TrialResultMonitor<RegressionMetrics> monitor = null; 265monitor = new TrialResultMonitor<RegressionMetrics>(channel, pipeline); 281var result = new CrossValidationExperimentResult<RegressionMetrics>(runDetails, bestResult); 286public override CrossValidationExperimentResult<RegressionMetrics> Execute(IDataView trainData, uint numberOfCVFolds, string labelColumnName = "Label", string samplingKeyColumn = null, IEstimator<ITransformer> preFeaturizer = null, IProgress<CrossValidationRunDetail<RegressionMetrics>> progressHandler = null) 318private protected override CrossValidationRunDetail<RegressionMetrics> GetBestCrossValRun(IEnumerable<CrossValidationRunDetail<RegressionMetrics>> results) 323private protected override RunDetail<RegressionMetrics> GetBestRun(IEnumerable<RunDetail<RegressionMetrics>> results) 340public static RunDetail<RegressionMetrics> Best(this IEnumerable<RunDetail<RegressionMetrics>> results, RegressionMetric metric = RegressionMetric.RSquared) 353public static CrossValidationRunDetail<RegressionMetrics> Best(this IEnumerable<CrossValidationRunDetail<RegressionMetrics>> results, RegressionMetric metric = RegressionMetric.RSquared) 411return Task.FromResult(new TrialResult<RegressionMetrics>() 430var metrics = _context.Regression.Evaluate(eval, metricManager.LabelColumn, scoreColumnName: metricManager.ScoreColumn); 437return Task.FromResult(new TrialResult<RegressionMetrics>() 469private double GetMetric(RegressionMetric metric, RegressionMetrics metrics)
AutoMLExperiment\IMetricManager.cs (1)
130var metric = context.Regression.Evaluate(eval, LabelColumn, ScoreColumn);
Experiment\MetricsAgents\RegressionMetricsAgent.cs (3)
9internal class RegressionMetricsAgent : IMetricsAgent<RegressionMetrics> 20public double GetScore(RegressionMetrics metrics) 64public RegressionMetrics EvaluateMetrics(IDataView data, string labelColumn, string groupIdColumn)
Experiment\Runners\CrossValSummaryRunner.cs (3)
132if (typeof(TMetrics) == typeof(RegressionMetrics)) 134var newMetrics = metrics.Select(x => x as RegressionMetrics); 137var result = new RegressionMetrics(
Tuner\SmacTuner.cs (1)
151var eval = _context.Regression.Evaluate(test);
Utils\BestResultUtil.cs (2)
21public static RunDetail<RegressionMetrics> GetBestRun(IEnumerable<RunDetail<RegressionMetrics>> results,
Microsoft.ML.AutoML.Samples (8)
AutoFit\RecommendationExperiment.cs (4)
33ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto() 44RunDetail<RegressionMetrics> bestRun = experimentResult.BestRun; 52RegressionMetrics testMetrics = mlContext.Recommendation().Evaluate(testDataViewWithBestScore, labelColumnName: LabelColumnName); 84private static void PrintMetrics(RegressionMetrics metrics)
AutoFit\RegressionExperiment.cs (4)
27ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto() 32RunDetail<RegressionMetrics> bestRun = experimentResult.BestRun; 40RegressionMetrics testMetrics = mlContext.Regression.Evaluate(testDataViewWithBestScore, labelColumnName: LabelColumnName); 68private static void PrintMetrics(RegressionMetrics metrics)
Microsoft.ML.AutoML.Tests (24)
AutoFitTests.cs (3)
530ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto() 540RunDetail<RegressionMetrics> bestRun = experimentResult.BestRun; 556var metrices = mlContext.Recommendation().Evaluate(testDataViewWithBestScore, labelColumnName: labelColumnName, scoreColumnName: scoreColumnName);
BestResultUtilTests.cs (10)
23var metrics1 = MetricsUtil.CreateRegressionMetrics(0.2, 0.2, 0.2, 0.2, 0.2); 24var metrics2 = MetricsUtil.CreateRegressionMetrics(0.3, 0.3, 0.3, 0.3, 0.3); 25var metrics3 = MetricsUtil.CreateRegressionMetrics(0.1, 0.1, 0.1, 0.1, 0.1); 27var runResults = new List<RunDetail<RegressionMetrics>>() 29new RunDetail<RegressionMetrics>(null, null, null, null, null, null), 30new RunDetail<RegressionMetrics>(null, null, null, null, metrics1, null), 31new RunDetail<RegressionMetrics>(null, null, null, null, metrics2, null), 32new RunDetail<RegressionMetrics>(null, null, null, null, metrics3, null), 43var runResults = new List<RunDetail<RegressionMetrics>>() 45new RunDetail<RegressionMetrics>(null, null, null, null, null, null),
MetricsAgentsTests.cs (5)
97var metrics = MetricsUtil.CreateRegressionMetrics(0.2, 0.3, 0.4, 0.5, 0.6); 107var metrics = MetricsUtil.CreateRegressionMetrics(0.2, 0.3, 0.4, 0.5, 0.6); 117var metrics = MetricsUtil.CreateRegressionMetrics(0, 0, 0, 0, 1); 177private static double GetScore(RegressionMetrics metrics, RegressionMetric metric) 199private static bool IsPerfectModel(RegressionMetrics metrics, RegressionMetric metric)
MetricsUtil.cs (2)
32public static RegressionMetrics CreateRegressionMetrics(double l1, 35return CreateInstance<RegressionMetrics>(l1, l2,
Utils\TaskAgnosticAutoFit.cs (2)
28internal interface IUniversalProgressHandler : IProgress<RunDetail<RegressionMetrics>>, IProgress<RunDetail<MulticlassClassificationMetrics>> 153var regressionMetrics = _context.Regression.Evaluate(result.ScoredTestData, labelColumnName: label);
Utils\TaskAgnosticIterationResult.cs (2)
50public TaskAgnosticIterationResult(RunDetail<RegressionMetrics> runDetail, string primaryMetricName = "RSquared") 74var supportedTypes = new[] { typeof(MulticlassClassificationMetrics), typeof(RegressionMetrics) };
Microsoft.ML.Data (5)
Evaluators\RegressionEvaluator.cs (2)
174public RegressionMetrics Evaluate(IDataView data, string label, string score) 187RegressionMetrics result;
TrainCatalog.cs (3)
599public RegressionMetrics Evaluate(IDataView data, string labelColumnName = DefaultColumnNames.Label, string scoreColumnName = DefaultColumnNames.Score) 623public IReadOnlyList<CrossValidationResult<RegressionMetrics>> CrossValidate( 629return result.Select(x => new CrossValidationResult<RegressionMetrics>(x.Model,
Microsoft.ML.Fairlearn (3)
Metrics\FairlearnMetricCatalog.cs (3)
187var groupMetric = new Dictionary<object, RegressionMetrics>(); 229RegressionMetrics metrics = _context.Regression.Evaluate(data, _labelColumn, _scoreColumn); 256RegressionMetrics metrics = _context.Regression.Evaluate(_eval, _labelColumn);
Microsoft.ML.IntegrationTests (9)
Common.cs (2)
266/// Check that a <see cref="RegressionMetrics"/> object is valid. 269public static void AssertMetrics(RegressionMetrics metrics)
Evaluation.cs (2)
253var metrics = mlContext.Recommendation().Evaluate(scoredData); 278var metrics = mlContext.Regression.Evaluate(scoredData);
Validation.cs (5)
48Assert.IsType<RegressionMetrics>(cvResult[0].Metrics); 136var trainMetrics = mlContext.Regression.Evaluate(scoredTrainData); 137var validMetrics = mlContext.Regression.Evaluate(scoredValidData); 161var evalResultOneRow = mlContext.Regression.Evaluate(scoredDataOneRow); 167var evalResultZeroRows = mlContext.Regression.Evaluate(scoredDataZeroRows);
Microsoft.ML.Predictor.Tests (1)
TestIniModels.cs (1)
544var results = mlContext.Regression.Evaluate(data);
Microsoft.ML.Recommender (3)
RecommenderCatalog.cs (3)
109public RegressionMetrics Evaluate(IDataView data, string labelColumnName = DefaultColumnNames.Label, string scoreColumnName = DefaultColumnNames.Score) 135public IReadOnlyList<CrossValidationResult<RegressionMetrics>> CrossValidate( 141return result.Select(x => new CrossValidationResult<RegressionMetrics>(x.Model, Evaluate(x.Scores, labelColumnName), x.Scores, x.Fold)).ToArray();
Microsoft.ML.Samples (48)
Dynamic\Trainers\Recommendation\MatrixFactorization.cs (2)
64var metrics = mlContext.Regression.Evaluate(transformedData, 125private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Recommendation\MatrixFactorizationWithOptions.cs (2)
88var metrics = mlContext.Regression.Evaluate(transformedData, 149private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastForest.cs (2)
62var metrics = mlContext.Regression.Evaluate(transformedTestData); 108private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastForestWithOptions.cs (2)
75var metrics = mlContext.Regression.Evaluate(transformedTestData); 121private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastTree.cs (2)
62var metrics = mlContext.Regression.Evaluate(transformedTestData); 108private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastTreeTweedie.cs (2)
62var metrics = mlContext.Regression.Evaluate(transformedTestData); 108private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastTreeTweedieWithOptions.cs (2)
77var metrics = mlContext.Regression.Evaluate(transformedTestData); 123private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\FastTreeWithOptions.cs (2)
78var metrics = mlContext.Regression.Evaluate(transformedTestData); 124private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\Gam.cs (2)
62var metrics = mlContext.Regression.Evaluate(transformedTestData); 108private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\GamWithOptions.cs (2)
73var metrics = mlContext.Regression.Evaluate(transformedTestData); 119private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LbfgsPoissonRegression.cs (2)
60var metrics = mlContext.Regression.Evaluate(transformedTestData); 106private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LbfgsPoissonRegressionWithOptions.cs (2)
74var metrics = mlContext.Regression.Evaluate(transformedTestData); 120private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LightGbm.cs (2)
63var metrics = mlContext.Regression.Evaluate(transformedTestData); 109private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (2)
62var metrics = mlContext.Regression.Evaluate( 75private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LightGbmWithOptions.cs (2)
82var metrics = mlContext.Regression.Evaluate(transformedTestData); 128private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (2)
71var metrics = mlContext.Regression.Evaluate( 84public static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OnlineGradientDescent.cs (2)
55var metrics = mlContext.Regression.Evaluate(transformedTestData); 97private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OnlineGradientDescentWithOptions.cs (2)
70var metrics = mlContext.Regression.Evaluate(transformedTestData); 113private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OrdinaryLeastSquares.cs (2)
59var metrics = mlContext.Regression.Evaluate(transformedTestData); 105private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OrdinaryLeastSquaresAdvanced.cs (2)
64var metrics = mlContext.Regression.Evaluate(dataWithPredictions); 76public static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptions.cs (2)
71var metrics = mlContext.Regression.Evaluate(transformedTestData); 117private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptionsAdvanced.cs (2)
68var metrics = mlContext.Regression.Evaluate(dataWithPredictions); 80public static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\Sdca.cs (2)
59var metrics = mlContext.Regression.Evaluate(transformedTestData); 105private static void PrintMetrics(RegressionMetrics metrics)
Dynamic\Trainers\Regression\SdcaWithOptions.cs (2)
75var metrics = mlContext.Regression.Evaluate(transformedTestData); 121private static void PrintMetrics(RegressionMetrics metrics)
Microsoft.ML.Samples.OneDal (4)
Program.cs (4)
116var trainingMetrics = mlContext.Regression.Evaluate(trainingPredictions, labelColumnName: labelName); 118var testingMetrics = mlContext.Regression.Evaluate(testingPredictions, labelColumnName: labelName); 144var trainingMetrics = mlContext.Regression.Evaluate(trainingPredictions, labelColumnName: labelName); 146var testingMetrics = mlContext.Regression.Evaluate(testingPredictions, labelColumnName: labelName);
Microsoft.ML.Tests (16)
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (1)
195var metrics = mlContext.Regression.Evaluate(model.Transform(testData), labelColumnName: "Target");
Scenarios\RegressionTest.cs (1)
44var metrics = context.Regression.Evaluate(predictions);
TrainerEstimators\MatrixFactorizationTests.cs (5)
125var metrices = mlContext.Recommendation().Evaluate(prediction, labelColumnName: labelColumnName, scoreColumnName: scoreColumnName); 247var metrics = mlContext.Recommendation().Evaluate(prediction, labelColumnName: nameof(MatrixElement.Value), 359var metrics = mlContext.Recommendation().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score"); 472var metrics = mlContext.Recommendation().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score"); 616var metrics = mlContext.Recommendation().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score");
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (9)
459var metrics = ML.Regression.Evaluate(prediction); 497var metrics = ML.Regression.Evaluate(prediction); 535var metrics = ML.Regression.Evaluate(prediction); 573var metrics = ML.Regression.Evaluate(prediction); 611var metrics = ML.Regression.Evaluate(prediction); 628var loadedMetrics = ML.Regression.Evaluate(loadedPrediction); 668var metrics = ML.Regression.Evaluate(prediction); 687var loadedMetrics = ML.Regression.Evaluate(loadedPrediction); 700var secondMetrics = ML.Regression.Evaluate(secondPrediction);
Microsoft.ML.Transforms (17)
MetricStatistics.cs (10)
78/// <typeparam name="T">The metric results type, such as <see cref="RegressionMetrics"/>.</typeparam> 86/// statistics over multiple observations of <see cref="RegressionMetrics"/>. 88public sealed class RegressionMetricsStatistics : IMetricsStatistics<RegressionMetrics> 91/// Summary statistics for <see cref="RegressionMetrics.MeanAbsoluteError"/>. 96/// Summary statistics for <see cref="RegressionMetrics.MeanSquaredError"/>. 101/// Summary statistics for <see cref="RegressionMetrics.RootMeanSquaredError"/>. 106/// Summary statistics for <see cref="RegressionMetrics.LossFunction"/>. 111/// Summary statistics for <see cref="RegressionMetrics.RSquared"/>. 128void IMetricsStatistics<RegressionMetrics>.Add(RegressionMetrics metrics)
PermutationFeatureImportanceExtensions.cs (7)
45/// <see cref="ImmutableArray"/> of <see cref="RegressionMetrics"/> objects is returned. See the sample below for an 74return PermutationFeatureImportance<TModel, RegressionMetrics, RegressionMetricsStatistics>.GetImportanceMetricsMatrix( 108/// <see cref="ImmutableArray"/> of <see cref="RegressionMetrics"/> objects is returned. See the sample below for an 146RegressionMetrics evaluationFunc(IDataView idv) => catalog.Evaluate(idv, labelColumnName); 161private static RegressionMetrics RegressionDelta( 162RegressionMetrics a, RegressionMetrics b)