Package | Description |
---|---|
smile.feature |
Feature generation, normalization and selection.
|
smile.regression |
Regression analysis.
|
smile.validation |
Model validation.
|
Class and Description |
---|
RegressionTrainer
Abstract regression model trainer.
|
Class and Description |
---|
GaussianProcessRegression
Gaussian Process for Regression.
|
GradientTreeBoost
Gradient boosting for regression.
|
GradientTreeBoost.Loss
Regression loss function.
|
GradientTreeBoost.Trainer
Trainer for GradientTreeBoost regression.
|
LASSO
Least absolute shrinkage and selection operator.
|
LASSO.Trainer
Trainer for LASSO regression.
|
OLS
Ordinary least squares.
|
RandomForest
Random forest for regression.
|
RandomForest.Trainer
Trainer for random forest.
|
RBFNetwork
Radial basis function network.
|
RBFNetwork.Trainer
Trainer for RBF networks.
|
Regression
Regression analysis includes any techniques for modeling and analyzing
the relationship between a dependent variable and one or more independent
variables.
|
RegressionTrainer
Abstract regression model trainer.
|
RegressionTree
Decision tree for regression.
|
RegressionTree.NodeOutput
An interface to calculate node output.
|
RegressionTree.Trainer
Trainer for regression tree.
|
RidgeRegression
Ridge Regression.
|
SVR
Support vector regression.
|
SVR.Trainer
Trainer for support vector regression.
|
Class and Description |
---|
Regression
Regression analysis includes any techniques for modeling and analyzing
the relationship between a dependent variable and one or more independent
variables.
|
RegressionTrainer
Abstract regression model trainer.
|
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