NeuralNetwork (deeplearning4j-nn 0.9.1 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(org.nd4j.linalg.dataset.api.iterator.DataSetIterator iterator, T... evaluations)` This method executes evaluation of the model against given iterator and evaluation implementations
`<T extends IEvaluation> T[]`	`doEvaluation(org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator iterator, T... evaluations)` This method executes evaluation of the model against given iterator and evaluation implementations
`void`	`fit(org.nd4j.linalg.dataset.api.DataSet dataSet)` This method fits model with a given DataSet
`void`	`fit(org.nd4j.linalg.dataset.api.iterator.DataSetIterator iterator)` This method fits model with a given DataSetIterator
`void`	`fit(org.nd4j.linalg.dataset.api.MultiDataSet dataSet)` This method fits model with a given MultiDataSet
`void`	`fit(org.nd4j.linalg.dataset.api.iterator.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
`org.nd4j.linalg.api.ndarray.INDArray`	`params()` This method returns model parameters as single INDArray
`org.nd4j.linalg.api.ndarray.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
```
org.nd4j.linalg.api.ndarray.INDArray params()
```
    This method returns model parameters as single INDArray
    
    Returns:
  - updaterState
```
org.nd4j.linalg.api.ndarray.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(org.nd4j.linalg.dataset.api.DataSet dataSet)
```
    This method fits model with a given DataSet
    
    Parameters:
    
    dataSet -
  - fit
```
void fit(org.nd4j.linalg.dataset.api.MultiDataSet dataSet)
```
    This method fits model with a given MultiDataSet
    
    Parameters:
    
    dataSet -
  - fit
```
void fit(org.nd4j.linalg.dataset.api.iterator.DataSetIterator iterator)
```
    This method fits model with a given DataSetIterator
    
    Parameters:
    
    iterator -
  - fit
```
void fit(org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator iterator)
```
    This method fits model with a given MultiDataSetIterator
    
    Parameters:
    
    iterator -
  - doEvaluation
```
<T extends IEvaluation> T[] doEvaluation(org.nd4j.linalg.dataset.api.iterator.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(org.nd4j.linalg.dataset.api.iterator.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