| Interface | Description |
|---|---|
| RegressionModel |
| Class | Description |
|---|---|
| GeneralizedLinearAlgorithm<M extends GeneralizedLinearModel> |
GeneralizedLinearAlgorithm implements methods to train a Generalized Linear Model (GLM).
|
| GeneralizedLinearModel |
GeneralizedLinearModel (GLM) represents a model trained using
GeneralizedLinearAlgorithm.
|
| IsotonicRegression |
Isotonic regression.
|
| IsotonicRegressionModel |
Regression model for isotonic regression.
|
| LabeledPoint |
Class that represents the features and labels of a data point.
|
| LassoModel |
Regression model trained using Lasso.
|
| LassoWithSGD |
Train a regression model with L1-regularization using Stochastic Gradient Descent.
|
| LinearRegressionModel |
Regression model trained using LinearRegression.
|
| LinearRegressionWithSGD |
Train a linear regression model with no regularization using Stochastic Gradient Descent.
|
| RidgeRegressionModel |
Regression model trained using RidgeRegression.
|
| RidgeRegressionWithSGD |
Train a regression model with L2-regularization using Stochastic Gradient Descent.
|
| StreamingLinearAlgorithm<M extends GeneralizedLinearModel,A extends GeneralizedLinearAlgorithm<M>> |
StreamingLinearAlgorithm implements methods for continuously
training a generalized linear model on streaming data,
and using it for prediction on (possibly different) streaming data.
|
| StreamingLinearRegressionWithSGD |
Train or predict a linear regression model on streaming data.
|