org.deeplearning4j.nn.api

Interface Model

All Known Subinterfaces:

Classifier, NeuralNetwork

All Known Implementing Classes:

AutoEncoder, BaseMultiLayerNetwork, BaseNeuralNetwork, DBN, DenoisingAutoEncoder, OutputLayer, RBM, SemanticHashing, StackedAutoEncoder, StackedDenoisingAutoEncoder

public interface Model

A Model is meant for predicting something from data. Note that this is not like supervised learning where there are labels attached to the examples.

Method Summary

Modifier and Type	Method and Description
void	fit(org.nd4j.linalg.api.ndarray.INDArray data) Fit the model to the given data
void	fit(org.nd4j.linalg.api.ndarray.INDArray data, Object[] params) Fit the model to the given data
void	iterate(org.nd4j.linalg.api.ndarray.INDArray input, Object[] params) Run one iteration
int	numParams() The number of parameters for the model
org.nd4j.linalg.api.ndarray.INDArray	params() Parameters of the model (if any)
double	score()
void	setParams(org.nd4j.linalg.api.ndarray.INDArray params) Set the parameters for this model.
org.nd4j.linalg.api.ndarray.INDArray	transform(org.nd4j.linalg.api.ndarray.INDArray data) Transform the data based on the model's output.

Method Detail

score

double score()

transform

org.nd4j.linalg.api.ndarray.INDArray transform(org.nd4j.linalg.api.ndarray.INDArray data)

Transform the data based on the model's output. This can be anything from a number to reconstructions.

Parameters:

data - the data to transform

Returns:

the transformed data

params

org.nd4j.linalg.api.ndarray.INDArray params()

Parameters of the model (if any)

Returns:

the parameters of the model

numParams

int numParams()

The number of parameters for the model

Returns:

the number of parameters for the model

setParams

void setParams(org.nd4j.linalg.api.ndarray.INDArray params)

Set the parameters for this model. This expects a linear ndarray which then be unpacked internally relative to the expected ordering of the model

Parameters:

params - the parameters for the model

fit

void fit(org.nd4j.linalg.api.ndarray.INDArray data,
         Object[] params)

Fit the model to the given data

Parameters:

data - the data to fit the model to

params - the params (mixed values)

fit

void fit(org.nd4j.linalg.api.ndarray.INDArray data)

Fit the model to the given data

Parameters:

data - the data to fit the model to

iterate

void iterate(org.nd4j.linalg.api.ndarray.INDArray input,
             Object[] params)

Run one iteration

Parameters:

input - the input to iterate on

params - the extra params for the neural network(k, corruption level, max epochs,...)