smile.regression

Class RBFNetwork.Trainer<T>

java.lang.Object

smile.regression.RegressionTrainer<T>

smile.regression.RBFNetwork.Trainer<T>

Enclosing class:

RBFNetwork<T>

public static class RBFNetwork.Trainer<T>
extends RegressionTrainer<T>

Trainer for RBF networks.

Constructor Summary

Constructors

Constructor and Description
Trainer(smile.math.distance.Metric<T> distance) Constructor.

Method Summary

Modifier and Type	Method and Description
RBFNetwork.Trainer	setNormalized(boolean normalized) Sets true to learn normalized RBF network.
RBFNetwork.Trainer	setNumCenters(int m) Sets the number of centers.
RBFNetwork.Trainer	setRBF(smile.math.rbf.RadialBasisFunction[] rbf) Sets the radial basis functions.
RBFNetwork.Trainer	setRBF(smile.math.rbf.RadialBasisFunction rbf, int m) Sets the radial basis function.
RBFNetwork<T>	train(T[] x, double[] y) Learns a regression model with given training data.
RBFNetwork<T>	train(T[] x, double[] y, T[] centers) Learns a RBF network with given centers.

Methods inherited from class smile.regression.RegressionTrainer

setAttributes

Methods inherited from class java.lang.Object

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

Constructor Detail

Trainer

public Trainer(smile.math.distance.Metric<T> distance)

Constructor.

Parameters:

distance - the distance metric functor.

Method Detail

setRBF

public RBFNetwork.Trainer setRBF(smile.math.rbf.RadialBasisFunction rbf,
                                 int m)

Sets the radial basis function.

Parameters:

rbf - the radial basis function.

m - the number of basis functions.

setRBF

public RBFNetwork.Trainer setRBF(smile.math.rbf.RadialBasisFunction[] rbf)

Sets the radial basis functions.

Parameters:

rbf - the radial basis functions.

setNumCenters

public RBFNetwork.Trainer setNumCenters(int m)

Sets the number of centers.

Parameters:

m - the number of centers.

setNormalized

public RBFNetwork.Trainer setNormalized(boolean normalized)

Sets true to learn normalized RBF network.

Parameters:

normalized - true to learn normalized RBF network.

train

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

Description copied from class: RegressionTrainer

Learns a regression model with given training data.

Specified by:

train in class RegressionTrainer<T>

Parameters:

x - the training instances.

y - the training response values.

Returns:

a trained regression model.

train

public RBFNetwork<T> train(T[] x,
                           double[] y,
                           T[] centers)

Learns a RBF network with given centers.

Parameters:

x - the training data.

y - the response variable.

centers - the centers of RBF functions.

Returns:

a trained RBF network