2 types derived from LinearModelParameters
Microsoft.ML.StandardTrainers (2)
Standard\LinearModelParameters.cs (2)
419public sealed partial class LinearBinaryModelParameters : LinearModelParameters, 572public abstract class RegressionModelParameters : LinearModelParameters
44 references to LinearModelParameters
Microsoft.ML.Mkl.Components (4)
SymSgdClassificationTrainer.cs (4)
223var linearInitPred = initPred as LinearModelParameters; 269public BinaryPredictionTransformer<TPredictor> Fit(IDataView trainData, LinearModelParameters modelParameters) 701private TPredictor TrainCore(IChannel ch, RoleMappedData data, LinearModelParameters predictor, int weightSetCount)
Microsoft.ML.StandardTrainers (39)
Standard\LinearModelParameters.cs (6)
65private readonly LinearModelParameters _pred; 80public WeightsCollection(LinearModelParameters pred) 332var first = (LinearModelParameters)models[0]; 343var sub = (LinearModelParameters)m;
Standard\LogisticRegression\LogisticRegression.cs (3)
187public BinaryPredictionTransformer<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>> Fit(IDataView trainData, LinearModelParameters modelParameters) 441var pred = srcPredictor as LinearModelParameters;
Standard\Online\AveragedLinear.cs (1)
154private protected AveragedTrainStateBase(IChannel ch, int numFeatures, LinearModelParameters predictor, AveragedLinearTrainer<TTransformer, TModel> parent)
Standard\Online\AveragedPerceptron.cs (2)
124public TrainState(IChannel ch, int numFeatures, LinearModelParameters predictor, AveragedPerceptronTrainer parent) 212private protected override TrainStateBase MakeState(IChannel ch, int numFeatures, LinearModelParameters predictor)
Standard\Online\LinearSvm.cs (2)
136public TrainState(IChannel ch, int numFeatures, LinearModelParameters predictor, LinearSvmTrainer parent) 320private protected override TrainStateBase MakeState(IChannel ch, int numFeatures, LinearModelParameters predictor)
Standard\Online\OnlineGradientDescent.cs (2)
102public TrainState(IChannel ch, int numFeatures, LinearModelParameters predictor, OnlineGradientDescentTrainer parent) 181private protected override TrainStateBase MakeState(IChannel ch, int numFeatures, LinearModelParameters predictor)
Standard\Online\OnlineLinear.cs (6)
83/// this, and return the instance via <see cref="MakeState(IChannel, int, LinearModelParameters)"/>. 123protected TrainStateBase(IChannel ch, int numFeatures, LinearModelParameters predictor, OnlineLinearTrainer<TTransformer, TModel> parent) 279if (initPredictor is LinearModelParameters initLinearPred) 280initLinearPred = (LinearModelParameters)initPredictor; 308public TTransformer Fit(IDataView trainData, LinearModelParameters modelParameters) 351private protected abstract TrainStateBase MakeState(IChannel ch, int numFeatures, LinearModelParameters predictor);
Standard\PoissonRegression\PoissonRegression.cs (3)
134public RegressionPredictionTransformer<PoissonRegressionModelParameters> Fit(IDataView trainData, LinearModelParameters linearModel) 139var modelParameters = (LinearModelParameters)srcPredictor;
Standard\SdcaBinary.cs (10)
76var linInitPred = (initPred as IWeaklyTypedCalibratedModelParameters)?.WeaklyTypedSubModel as LinearModelParameters; 77linInitPred = linInitPred ?? initPred as LinearModelParameters; 84private protected abstract TModel TrainCore(IChannel ch, RoleMappedData data, LinearModelParameters predictor, int weightSetCount); 322private protected sealed override TModel TrainCore(IChannel ch, RoleMappedData data, LinearModelParameters predictor, int weightSetCount) 2013public BinaryPredictionTransformer<TModel> Fit(IDataView trainData, LinearModelParameters modelParameters) 2019private protected override TModel TrainCore(IChannel ch, RoleMappedData data, LinearModelParameters predictor, int weightSetCount) 2205/// It's used at the end of <see cref="TrainCore(IChannel, RoleMappedData, LinearModelParameters, int)"/> to finalize the trained model. 2310/// Given weights and bias trained in <see cref="SgdBinaryTrainerBase{TModelParameters}.TrainCore(IChannel, RoleMappedData, LinearModelParameters, int)"/>, 2437/// a calibrator would be added after <see cref="SgdBinaryTrainerBase{TModelParameters}.TrainCore(IChannel, RoleMappedData, LinearModelParameters, int)"/>
Standard\StochasticTrainerBase.cs (4)
38var linInitPred = (initPred as IWeaklyTypedCalibratedModelParameters)?.WeaklyTypedSubModel as LinearModelParameters; 40linInitPred = linInitPred ?? initPred as LinearModelParameters; 92private protected abstract TModel TrainCore(IChannel ch, RoleMappedData data, LinearModelParameters predictor, int weightSetCount);
Microsoft.ML.TestFramework (1)
EnvironmentExtensions.cs (1)
21env.ComponentCatalog.RegisterAssembly(typeof(LinearModelParameters).Assembly); // ML.StandardTrainers