internal SdcaRegressionTrainer(IHostEnvironment env, Options options, string featureColumn, string labelColumn, string weightColumn = null) : base(env, options, TrainerUtils.MakeR4ScalarColumn(labelColumn), TrainerUtils.MakeR4ScalarWeightColumn(weightColumn)) { Host.CheckValue(labelColumn, nameof(labelColumn)); Host.CheckValue(featureColumn, nameof(featureColumn)); _loss = options.LossFunction.CreateComponent(env); Loss = _loss; }
/// <summary> /// Initializes a new instance of <see cref="OlsTrainer"/> /// </summary> internal OlsTrainer(IHostEnvironment env, Options options) : base(Contracts.CheckRef(env, nameof(env)).Register(LoadNameValue), TrainerUtils.MakeR4VecFeature(options.FeatureColumnName), TrainerUtils.MakeR4ScalarColumn(options.LabelColumnName), TrainerUtils.MakeR4ScalarWeightColumn(options.ExampleWeightColumnName)) { Host.CheckValue(options, nameof(options)); Host.CheckUserArg(options.L2Regularization >= 0, nameof(options.L2Regularization), "L2 regularization term cannot be negative"); _l2Weight = options.L2Regularization; _perParameterSignificance = options.CalculateStatistics; }
/// <summary> /// Initializes a new instance of <see cref="OrdinaryLeastSquaresRegressionTrainer"/> /// </summary> internal OrdinaryLeastSquaresRegressionTrainer(IHostEnvironment env, Options options) : base(Contracts.CheckRef(env, nameof(env)).Register(LoadNameValue), TrainerUtils.MakeR4VecFeature(options.FeatureColumnName), TrainerUtils.MakeR4ScalarColumn(options.LabelColumnName), TrainerUtils.MakeR4ScalarWeightColumn(options.ExampleWeightColumnName)) { Host.CheckValue(options, nameof(options)); Host.CheckUserArg(options.L2Weight >= 0, nameof(options.L2Weight), "L2 regularization term cannot be negative"); _l2Weight = options.L2Weight; _perParameterSignificance = options.PerParameterSignificance; }
/// <summary> /// Initializes a new instance of <see cref="PoissonRegression"/> /// </summary> /// <param name="env">The environment to use.</param> /// <param name="labelColumn">The name of the label column.</param> /// <param name="featureColumn">The name of the feature column.</param> /// <param name="weights">The name for the example weight column.</param> /// <param name="l1Weight">Weight of L1 regularizer term.</param> /// <param name="l2Weight">Weight of L2 regularizer term.</param> /// <param name="optimizationTolerance">Threshold for optimizer convergence.</param> /// <param name="memorySize">Memory size for <see cref="LogisticRegression"/>. Low=faster, less accurate.</param> /// <param name="enforceNoNegativity">Enforce non-negative weights.</param> internal PoissonRegression(IHostEnvironment env, string labelColumn = DefaultColumnNames.Label, string featureColumn = DefaultColumnNames.Features, string weights = null, float l1Weight = Options.Defaults.L1Weight, float l2Weight = Options.Defaults.L2Weight, float optimizationTolerance = Options.Defaults.OptTol, int memorySize = Options.Defaults.MemorySize, bool enforceNoNegativity = Options.Defaults.EnforceNonNegativity) : base(env, featureColumn, TrainerUtils.MakeR4ScalarColumn(labelColumn), weights, l1Weight, l2Weight, optimizationTolerance, memorySize, enforceNoNegativity) { Host.CheckNonEmpty(featureColumn, nameof(featureColumn)); Host.CheckNonEmpty(labelColumn, nameof(labelColumn)); }
/// <summary> /// Initializes a new instance of <see cref="SdcaRegressionTrainer"/> /// </summary> /// <param name="env">The environment to use.</param> /// <param name="labelColumn">The label, or dependent variable.</param> /// <param name="featureColumn">The features, or independent variables.</param> /// <param name="weights">The optional example weights.</param> /// <param name="loss">The custom loss.</param> /// <param name="l2Const">The L2 regularization hyperparameter.</param> /// <param name="l1Threshold">The L1 regularization hyperparameter. Higher values will tend to lead to more sparse model.</param> /// <param name="maxIterations">The maximum number of passes to perform over the data.</param> internal SdcaRegressionTrainer(IHostEnvironment env, string labelColumn = DefaultColumnNames.Label, string featureColumn = DefaultColumnNames.Features, string weights = null, ISupportSdcaRegressionLoss loss = null, float?l2Const = null, float?l1Threshold = null, int?maxIterations = null) : base(env, featureColumn, TrainerUtils.MakeR4ScalarColumn(labelColumn), TrainerUtils.MakeR4ScalarWeightColumn(weights), l2Const, l1Threshold, maxIterations) { Host.CheckNonEmpty(featureColumn, nameof(featureColumn)); Host.CheckNonEmpty(labelColumn, nameof(labelColumn)); _loss = loss ?? Args.LossFunction.CreateComponent(env); Loss = _loss; }
/// <summary> /// Initializes a new instance of <see cref="PoissonRegression"/> /// </summary> internal PoissonRegression(IHostEnvironment env, Options options) : base(env, options, TrainerUtils.MakeR4ScalarColumn(options.LabelColumn)) { }
internal OnlineGradientDescentTrainer(IHostEnvironment env, Options options) : base(options, env, UserNameValue, TrainerUtils.MakeR4ScalarColumn(options.LabelColumnName)) { LossFunction = options.LossFunction ?? options.LossFunctionFactory.CreateComponent(env); }
/// <summary> /// Initializes a new instance of <see cref="PoissonRegression"/> /// </summary> internal PoissonRegression(IHostEnvironment env, Arguments args) : base(env, args, TrainerUtils.MakeR4ScalarColumn(args.LabelColumn)) { }