modelSet< T > Class Template Reference

#include <modelSet.h>

Inheritance diagram for modelSet< T >:

Collaboration diagram for modelSet< T >:

Public Member Functions
	modelSet ()
virtual	~modelSet ()
virtual bool	train (const std::vector< trainingExampleTemplate< T > > &trainingSet)
bool	reset ()
std::vector< T >	run (const std::vector< T > &inputVector)
std::string	getJSON ()
void	writeJSON (const std::string &filepath)
bool	putJSON (const std::string &jsonMessage)
bool	readJSON (const std::string &filepath)

Protected Member Functions
void	threadTrain (std::size_t i, const std::vector< trainingExampleTemplate< T > > &training_set)

Protected Attributes
std::vector< baseModel< T > * >	myModelSet
int	numInputs
std::vector< std::string >	inputNames
int	numOutputs
bool	isTraining
bool	isTrained

Detailed Description

template<typename T>
class modelSet< T >

This class holds a set of models with the same or different algorithms.

Constructor & Destructor Documentation

modelSet()

template<typename T >

modelSet< T >::modelSet

No arguments, don't create any models yet

~modelSet()

template<typename T >

modelSet< T >::~modelSet

virtual

Member Function Documentation

getJSON()

template<typename T >

std::string modelSet< T >::getJSON

Get a JSON representation of the model

Returns

Styled string JSON representation

putJSON()

template<typename T >

bool modelSet< T >::putJSON

(

const std::string &

jsonMessage

)

configure empty model with string. See getJSON()

readJSON()

template<typename T >

bool modelSet< T >::readJSON

(

const std::string &

filepath

)

read a JSON file at file path and build a modelSet from it

reset()

template<typename T >

bool modelSet< T >::reset

reset to pre-training state

run()

template<typename T >

std::vector< T > modelSet< T >::run

(

const std::vector< T > &

inputVector

)

Generate an output value from a single input vector.

Will return an error if training in progress.

Parameters

vector

A standard vector of type T that is the input for classification or regression.

Returns

vector A vector type T that are the predictions for each model in the set.

threadTrain()

template<typename T >

void modelSet< T >::threadTrain ( std::size_t  i, const std::vector< trainingExampleTemplate< T > > &  training_set  )

protected

train()

template<typename T >

bool modelSet< T >::train ( const std::vector< trainingExampleTemplate< T > > &  trainingSet )

virtual

Train on a specified set, causes creation if not created

Reimplemented in regressionTemplate< T >, and classificationTemplate< T >.

writeJSON()

template<typename T >

void modelSet< T >::writeJSON

(

const std::string &

filepath

)

Write a JSON model description to specified file path

Parameters

file

path

Member Data Documentation

inputNames

template<typename T >

std::vector<std::string> modelSet< T >::inputNames

protected

isTrained

template<typename T >

bool modelSet< T >::isTrained

protected

isTraining

template<typename T >

bool modelSet< T >::isTraining

protected

myModelSet

template<typename T >

std::vector<baseModel<T>*> modelSet< T >::myModelSet

protected

numInputs

template<typename T >

int modelSet< T >::numInputs

protected

numOutputs

template<typename T >

int modelSet< T >::numOutputs

protected

---

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

• src/modelSet.h
• src/modelSet.cpp