NeuralNet::TrainingData< X, Y > Class Template Reference

Public Member Functions
	TrainingData (X xTrain, Y yTrain, X xTest=X(), Y yTest=Y())
	Construct a new Training Data object. This object is used to store the inputs and labels data, it comes with a set of methods to manipulate the data to your liking for better training optimization.
std::vector< std::pair< X, Y > >	getMiniBatches ()
void	batch (int batchSize, bool stratified=false, bool shuffle=false, bool dropLast=false, bool verbose=false)
	This method will separate the inputs and labels data into batches of the specified size.

Friends
class	Network

Constructor & Destructor Documentation

TrainingData()

template<typename X , typename Y >

NeuralNet::TrainingData< X, Y >::TrainingData ( X xTrain, Y yTrain, X xTest = X(), Y yTest = Y() )

inline

Construct a new Training Data object. This object is used to store the inputs and labels data, it comes with a set of methods to manipulate the data to your liking for better training optimization.

Parameters

inputs_data	The inputs data
labels_data	The labels data

Note

The inputs and labels data must have the same size

Member Function Documentation

batch()

template<typename X , typename Y >

void NeuralNet::TrainingData< X, Y >::batch ( int batchSize, bool stratified = false, bool shuffle = false, bool dropLast = false, bool verbose = false )

inline

This method will separate the inputs and labels data into batches of the specified size.

Parameters

batchSize

The number of elements in each batch

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The documentation for this class was generated from the following file:

• /github/workspace/src/NeuralNet/data/TrainingData.hpp