Package org.tribuo.math

Interface FeedForwardParameters

All Superinterfaces:

Parameters, Serializable

All Known Implementing Classes:

FMParameters, LinearParameters

public interface FeedForwardParameters
extends Parameters

A Parameters for models which make a single prediction like logistic regressions and neural networks.

Method Summary

Modifier and Type	Method	Description
FeedForwardParameters	copy()	Returns a copy of the parameters.
Tensor[]	gradients(com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> score, SGDVector features)	Generates the parameter gradients given the loss, output gradient and input features.
DenseVector	predict(SGDVector example)	Generates an un-normalized prediction by feeding the features through the parameters.

Methods inherited from interface org.tribuo.math.Parameters

get, getEmptyCopy, merge, set, update

Method Details

predict

DenseVector predict(SGDVector example)

Generates an un-normalized prediction by feeding the features through the parameters.

Parameters:

example - The features.

Returns:

The prediction.

gradients

Tensor[] gradients(com.oracle.labs.mlrg.olcut.util.Pair<Double,SGDVector> score,
 SGDVector features)

Generates the parameter gradients given the loss, output gradient and input features.

Parameters:

score - The loss and gradient.

features - The input features.

Returns:

The parameter gradient array.

copy

FeedForwardParameters copy()

Returns a copy of the parameters.

Returns:

A copy of the model parameters.