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