seriesClassificationTemplate< T > Class Template Reference

#include <seriesClassification.h>

Collaboration diagram for seriesClassificationTemplate< T >:

Classes
struct	minMax

Public Member Functions
	seriesClassificationTemplate ()
	~seriesClassificationTemplate ()
bool	train (const std::vector< trainingSeriesTemplate< T > > &seriesSet)
void	reset ()
std::string	run (const std::vector< std::vector< T > > &inputSeries)
T	run (const std::vector< std::vector< T > > &inputSeries, std::string label)
std::string	runParallel (const std::vector< std::vector< T > > &inputSeries)
T	runParallel (const std::vector< std::vector< T > > &inputSeries, std::string label)
std::string	runContinuous (const std::vector< T > &inputVector)
std::vector< T >	getCosts () const
std::size_t	getMinLength () const
std::size_t	getMinLength (std::string label) const
std::size_t	getMaxLength () const
std::size_t	getMaxLength (std::string label) const
minMax< T >	calculateCosts (std::string label) const
minMax< T >	calculateCosts (std::string label1, std::string label2) const

Detailed Description

template<typename T>
class seriesClassificationTemplate< T >

Class for containing time series classifiers.

Currently only (fast)DTW.

Constructor & Destructor Documentation

seriesClassificationTemplate()

template<typename T >

seriesClassificationTemplate< T >::seriesClassificationTemplate

Constructor, no params

~seriesClassificationTemplate()

template<typename T >

seriesClassificationTemplate< T >::~seriesClassificationTemplate

Member Function Documentation

calculateCosts() [1/2]

template<typename T >

seriesClassificationTemplate< T >::template minMax< T > seriesClassificationTemplate< T >::calculateCosts

(

std::string

label

)

const

Calculate minimum and maximum cost between examples in a label.

Parameters

string

Label to calculate

Returns

minMax struct containing min and max

calculateCosts() [2/2]

template<typename T >

seriesClassificationTemplate< T >::template minMax< T > seriesClassificationTemplate< T >::calculateCosts	(	std::string	label1,
		std::string	label2
	)		const

Calculate minimum and maximum cost between examples in one label and examples in a second.

Parameters

string	first label to compare
string	second label to compare

Returns

minMax struct containing min and max

getCosts()

template<typename T >

std::vector< T > seriesClassificationTemplate< T >::getCosts

Get the costs that were calculated by the run method

Returns

A vector of floats or doubles, the cost of matching to each training series

getMaxLength() [1/2]

template<typename T >

std::size_t seriesClassificationTemplate< T >::getMaxLength

Get maximum training series length

Returns

The maximum length training series

getMaxLength() [2/2]

template<typename T >

std::size_t seriesClassificationTemplate< T >::getMaxLength

(

std::string

label

)

const

Get maximum training series length from a specified label

Parameters

string

The label to check

Returns

The maximum length training series of that label

getMinLength() [1/2]

template<typename T >

std::size_t seriesClassificationTemplate< T >::getMinLength

Get minimum training series length

Returns

The minimum length training series

getMinLength() [2/2]

template<typename T >

std::size_t seriesClassificationTemplate< T >::getMinLength

(

std::string

label

)

const

Get minimum training series length from a specified label

Parameters

string

The label to check

Returns

The minimum length training series of that label

reset()

template<typename T >

void seriesClassificationTemplate< T >::reset

Reset model to its initial state, forget all costs and training data

run() [1/2]

template<typename T >

std::string seriesClassificationTemplate< T >::run

(

const std::vector< std::vector< T > > &

inputSeries

)

Compare an input series to the stored training series

Parameters

std::vector<std::vector>

vector of vectors, either float or double input data

Returns

The label of the closest training series.

run() [2/2]

template<typename T >

T seriesClassificationTemplate< T >::run	(	const std::vector< std::vector< T > > &	inputSeries,
		std::string	label
	)

Compare an input series to all of the stored series with a specified label

Parameters

std::vector<std::vector>	either float or double input data
String	label to compare with

Returns

The lowest cost match, float or double

runContinuous()

template<typename T >

std::string seriesClassificationTemplate< T >::runContinuous

(

const std::vector< T > &

inputVector

)

Compare an input series to all of the stored series with a specified label

Parameters

std::vector<T>

one frame either float or double input data

Returns

The lowest cost match, float or double

runParallel() [1/2]

template<typename T >

std::string seriesClassificationTemplate< T >::runParallel

(

const std::vector< std::vector< T > > &

inputSeries

)

Compare an input series to the stored training series. Parallel processing

Parameters

std::vector<std::vector>

vector of vectors, either float or double input data

Returns

The label of the closest training series.

runParallel() [2/2]

template<typename T >

T seriesClassificationTemplate< T >::runParallel	(	const std::vector< std::vector< T > > &	inputSeries,
		std::string	label
	)

Compare an input series to all of the stored series with a specified label. Parallel processing

Parameters

std::vector<std::vector>	either float or double input data
String	label to compare with

Returns

The lowest cost match, float or double

train()

template<typename T >

bool seriesClassificationTemplate< T >::train

(

const std::vector< trainingSeriesTemplate< T > > &

seriesSet

)

Train on a specified set of trainingSeries

Parameters

std::vector<trainingSeries>

A vector of training series

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

• src/seriesClassification.h
• src/seriesClassification.cpp