smile.regression

Class RegressionTrainer<T>

java.lang.Object

smile.regression.RegressionTrainer<T>

Type Parameters:

T - the type of input object.

Direct Known Subclasses:

GaussianProcessRegression.Trainer, GradientTreeBoost.Trainer, LASSO.Trainer, NeuralNetwork.Trainer, OLS.Trainer, RandomForest.Trainer, RBFNetwork.Trainer, RegressionTree.Trainer, RidgeRegression.Trainer, RLS.Trainer, SVR.Trainer

public abstract class RegressionTrainer<T>
extends java.lang.Object

Abstract regression model trainer.

Constructor Summary

Constructors

Constructor and Description
RegressionTrainer() Constructor.
RegressionTrainer(smile.data.Attribute[] attributes) Constructor.

Method Summary

Modifier and Type	Method and Description
void	setAttributes(smile.data.Attribute[] attributes) Sets feature attributes.
abstract Regression<T>	train(T[] x, double[] y) Learns a regression model with given training data.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

RegressionTrainer

public RegressionTrainer()

Constructor.

RegressionTrainer

public RegressionTrainer(smile.data.Attribute[] attributes)

Constructor.

Parameters:

attributes - the attributes of independent variable.

Method Detail

setAttributes

public void setAttributes(smile.data.Attribute[] attributes)

Sets feature attributes. This is optional since most regression models can only work on real-valued attributes.

Parameters:

attributes - the feature attributes.

train

public abstract Regression<T> train(T[] x,
                                    double[] y)

Learns a regression model with given training data.

Parameters:

x - the training instances.

y - the training response values.

Returns:

a trained regression model.