NeuralNetwork (deeplearning4j-nn 1.0.0-M1.1 API)

All Known Implementing Classes:

ComputationGraph, MultiLayerNetwork
```
public interface NeuralNetwork
```
Author:

raver119

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`<T extends IEvaluation> T[]`	`doEvaluation(DataSetIterator iterator, T... evaluations)` This method executes evaluation of the model against given iterator and evaluation implementations
`<T extends IEvaluation> T[]`	`doEvaluation(MultiDataSetIterator iterator, T... evaluations)` This method executes evaluation of the model against given iterator and evaluation implementations
`void`	`fit(DataSet dataSet)` This method fits model with a given DataSet
`void`	`fit(DataSetIterator iterator)` This method fits model with a given DataSetIterator
`void`	`fit(MultiDataSet dataSet)` This method fits model with a given MultiDataSet
`void`	`fit(MultiDataSetIterator iterator)` This method fits model with a given MultiDataSetIterator
`ConvexOptimizer`	`getOptimizer()` This method returns Optimizer used for training
`void`	`init()` This method does initialization of model PLEASE NOTE: All implementations should track own state, to avoid double spending
`INDArray`	`params()` This method returns model parameters as single INDArray
`INDArray`	`updaterState()` This method returns updater state (if applicable), null otherwise

- Method Detail
  - init
```
void init()
```
    This method does initialization of model PLEASE NOTE: All implementations should track own state, to avoid double spending
  - params
```
INDArray params()
```
    This method returns model parameters as single INDArray
    
    Returns:
  - updaterState
```
INDArray updaterState()
```
    This method returns updater state (if applicable), null otherwise
    
    Returns:
  - getOptimizer
```
ConvexOptimizer getOptimizer()
```
    This method returns Optimizer used for training
    
    Returns:
  - fit
```
void fit(DataSet dataSet)
```
    This method fits model with a given DataSet
    
    Parameters:
    
    dataSet -
  - fit
```
void fit(MultiDataSet dataSet)
```
    This method fits model with a given MultiDataSet
    
    Parameters:
    
    dataSet -
  - fit
```
void fit(DataSetIterator iterator)
```
    This method fits model with a given DataSetIterator
    
    Parameters:
    
    iterator -
  - fit
```
void fit(MultiDataSetIterator iterator)
```
    This method fits model with a given MultiDataSetIterator
    
    Parameters:
    
    iterator -
  - doEvaluation
```
<T extends IEvaluation> T[] doEvaluation(DataSetIterator iterator,
                                         T... evaluations)
```
    This method executes evaluation of the model against given iterator and evaluation implementations
    
    Parameters:
    
    iterator -
  - doEvaluation
```
<T extends IEvaluation> T[] doEvaluation(MultiDataSetIterator iterator,
                                         T... evaluations)
```
    This method executes evaluation of the model against given iterator and evaluation implementations
    
    Parameters:
    
    iterator -

Interface NeuralNetwork

Method Summary

Method Detail

init

params

updaterState

getOptimizer

fit

fit

fit

fit

doEvaluation

doEvaluation