21 references to LossFunctionType
Microsoft.ML.AutoML (2)
TrainerExtensions\SweepableParams.cs (2)
128new SweepableDiscreteParam(nameof(MatrixFactorizationTrainer.Options.LossFunction), new object[] { MatrixFactorizationTrainer.LossFunctionType.SquareLossRegression, MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass }),
Microsoft.ML.CodeGenerator.Tests (2)
ApprovalTests\ConsoleCodeGeneratorTests.cs (1)
554{nameof(MatrixFactorizationTrainer.Options.LossFunction), MatrixFactorizationTrainer.LossFunctionType.SquareLossRegression },
TrainerGeneratorTests.cs (1)
309{nameof(MatrixFactorizationTrainer.Options.LossFunction), MatrixFactorizationTrainer.LossFunctionType.SquareLossRegression },
Microsoft.ML.Recommender (13)
MatrixFactorizationTrainer.cs (11)
165/// Two values are allowed, <see cref="LossFunctionType.SquareLossRegression"/> or <see cref="LossFunctionType.SquareLossOneClass"/>. 166/// The <see cref="LossFunctionType.SquareLossRegression"/> means traditional collaborative filtering problem with squared loss. 167/// The <see cref="LossFunctionType.SquareLossOneClass"/> triggers one-class matrix factorization for implicit-feedback recommendation problem. 171[TlcModule.SweepableDiscreteParam("LossFunction", new object[] { LossFunctionType.SquareLossRegression, LossFunctionType.SquareLossOneClass })] 172public LossFunctionType LossFunction = Defaults.LossFunction; 222/// Importance of unobserved entries' loss in one-class matrix factorization. Applicable if <see cref="LossFunction"/> set to <see cref="LossFunctionType.SquareLossOneClass"/> 242/// Desired negative entries value in one-class matrix factorization. Applicable if <see cref="LossFunction"/> set to <see cref="LossFunctionType.SquareLossOneClass"/> 283public const LossFunctionType LossFunction = LossFunctionType.SquareLossRegression;
RecommenderCatalog.cs (2)
85/// To invoke one-class matrix factorization, user needs to specify <see cref="MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass"/>. 86/// The default setting <see cref="MatrixFactorizationTrainer.LossFunctionType.SquareLossRegression"/> is for standard matrix factorization problem.
Microsoft.ML.Samples (1)
Dynamic\Trainers\Recommendation\OneClassMatrixFactorizationWithOptions.cs (1)
62LossFunction = MatrixFactorizationTrainer.LossFunctionType
Microsoft.ML.Tests (3)
TrainerEstimators\MatrixFactorizationTests.cs (3)
454LossFunction = MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass, 598LossFunction = MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass, 670LossFunction = MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass