22 references to Recommendation
Microsoft.ML.AutoML (2)
SweepableEstimator\Estimators\MatrixFactorization.cs (1)
11
return context.
Recommendation
().Trainers.MatrixFactorization(param.LabelColumnName, param.MatrixColumnIndexColumnName, param.MatrixRowIndexColumnName, param.ApproximationRank, param.LearningRate, param.NumberOfIterations);
TrainerExtensions\RecommendationTrainerExtensions.cs (1)
22
return mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
Microsoft.ML.AutoML.Samples (1)
AutoFit\RecommendationExperiment.cs (1)
52
RegressionMetrics testMetrics = mlContext.
Recommendation
().Evaluate(testDataViewWithBestScore, labelColumnName: LabelColumnName);
Microsoft.ML.AutoML.Tests (1)
AutoFitTests.cs (1)
556
var metrices = mlContext.
Recommendation
().Evaluate(testDataViewWithBestScore, labelColumnName: labelColumnName, scoreColumnName: scoreColumnName);
Microsoft.ML.IntegrationTests (2)
Evaluation.cs (2)
237
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(
253
var metrics = mlContext.
Recommendation
().Evaluate(scoredData);
Microsoft.ML.Samples (3)
Dynamic\Trainers\Recommendation\MatrixFactorization.cs (1)
34
var pipeline = mlContext.
Recommendation
().Trainers.
Dynamic\Trainers\Recommendation\MatrixFactorizationWithOptions.cs (1)
60
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(
Dynamic\Trainers\Recommendation\OneClassMatrixFactorizationWithOptions.cs (1)
66
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(
Microsoft.ML.Tests (13)
TrainerEstimators\MatrixFactorizationTests.cs (13)
49
var est = ML.
Recommendation
().Trainers.MatrixFactorization(options);
84
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
125
var metrices = mlContext.
Recommendation
().Evaluate(prediction, labelColumnName: labelColumnName, scoreColumnName: scoreColumnName);
228
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
247
var metrics = mlContext.
Recommendation
().Evaluate(prediction, labelColumnName: nameof(MatrixElement.Value),
340
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
359
var metrics = mlContext.
Recommendation
().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score");
463
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
472
var metrics = mlContext.
Recommendation
().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score");
607
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
616
var metrics = mlContext.
Recommendation
().Evaluate(prediction, labelColumnName: "Value", scoreColumnName: "Score");
673
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);
787
var pipeline = mlContext.
Recommendation
().Trainers.MatrixFactorization(options);