org.ea.javacnn.layers

Interface Layer

All Known Implementing Classes:

ConvolutionLayer, DropoutLayer, FullyConnectedLayer, InputLayer, LocalResponseNormalizationLayer, LossLayer, MaxoutLayer, PoolingLayer, RectifiedLinearUnitsLayer, RegressionLayer, SigmoidLayer, SoftMaxLayer, SVMLayer, TanhLayer

public interface Layer

A convolution neural network is built of layers that the data traverses back and forth in order to predict what the network sees in the data.

Method Summary

Modifier and Type	Method and Description
void	backward()
DataBlock	forward(DataBlock db, boolean training)
java.util.List<BackPropResult>	getBackPropagationResult()

Method Detail

forward

DataBlock forward(DataBlock db,
                  boolean training)

backward

void backward()

getBackPropagationResult

java.util.List<BackPropResult> getBackPropagationResult()