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Class Summary | |
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DecisionTreeRegressionModel | :: Experimental ::
Decision tree model for regression. |
DecisionTreeRegressor | :: Experimental ::
Decision tree learning algorithm
for regression. |
GBTRegressionModel | :: Experimental :: |
GBTRegressor | :: Experimental ::
Gradient-Boosted Trees (GBTs)
learning algorithm for regression. |
LeastSquaresAggregator | LeastSquaresAggregator computes the gradient and loss for a Least-squared loss function, as used in linear regression for samples in sparse or dense vector in a online fashion. |
LeastSquaresCostFun | LeastSquaresCostFun implements Breeze's DiffFunction[T] for Least Squares cost. |
LinearRegression | :: Experimental :: Linear regression. |
LinearRegressionModel | :: Experimental ::
Model produced by LinearRegression . |
RandomForestRegressionModel | :: Experimental ::
Random Forest model for regression. |
RandomForestRegressor | :: Experimental ::
Random Forest learning algorithm for regression. |
RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType,M>> | :: DeveloperApi :: |
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