Uses of Class
org.tribuo.regression.Regressor.DimensionTuple
Packages that use Regressor.DimensionTuple
Package
Description
Provides classes and infrastructure for regression problems with single or multiple output dimensions.
Provides implementations of sparse linear regression using various forms of regularisation penalty.
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Uses of Regressor.DimensionTuple in org.tribuo.regressionClasses in org.tribuo.regression that implement interfaces with type arguments of type Regressor.DimensionTupleMethods in org.tribuo.regression that return Regressor.DimensionTupleModifier and TypeMethodDescriptionRegressor.DimensionTuple.copy()Regressor.getDimension(int idx) Returns a dimension tuple for the requested dimension index.Methods in org.tribuo.regression that return types with arguments of type Regressor.DimensionTupleModifier and TypeMethodDescriptionRegressor.DimensionTuple.getDimension(String name) Regressor.getDimension(String name) Returns a dimension tuple for the requested dimension, or optional empty if it's not valid.Regressor.DimensionTuple.iterator()Regressor.iterator()Constructors in org.tribuo.regression with parameters of type Regressor.DimensionTupleModifierConstructorDescriptionRegressor(Regressor.DimensionTuple[] dimensions) Constructs a regressor from the supplied dimension tuples.
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Uses of Regressor.DimensionTuple in org.tribuo.regression.implMethods in org.tribuo.regression.impl that return Regressor.DimensionTupleModifier and TypeMethodDescriptionprotected abstract Regressor.DimensionTupleSkeletalIndependentRegressionModel.scoreDimension(int dimensionIdx, SparseVector features) Makes a prediction for a single dimension.protected abstract Regressor.DimensionTupleSkeletalIndependentRegressionSparseModel.scoreDimension(int dimensionIdx, SparseVector features) Makes a prediction for a single dimension.
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Uses of Regressor.DimensionTuple in org.tribuo.regression.slmMethods in org.tribuo.regression.slm that return Regressor.DimensionTupleModifier and TypeMethodDescriptionprotected Regressor.DimensionTupleSparseLinearModel.scoreDimension(int dimensionIdx, SparseVector features)