gurls::GurlsWrapper< T > Class Template Reference

GurlsWrapper is the base class for all gurls++ wrappers.

#include <wrapper.h>

Inheritance diagram for gurls::GurlsWrapper< T >:

Collaboration diagram for gurls::GurlsWrapper< T >:

List of all members.

Public Types
enum	ProblemType { CLASSIFICATION, REGRESSION }
Public Member Functions
virtual T	eval (const gVec< T > &X, unsigned long *index=NULL)
	Estimates label for a new input point.
virtual gMat2D< T > *	eval (const gMat2D< T > &X)=0
	Estimates label for an input matrix.
virtual const GurlsOptionsList &	getOpt () const
	Returns a const reference to the options structure.
	GurlsWrapper (const std::string &name)
	Constructor.
virtual void	loadModel (const std::string &fileName)
	Loads a computed model from a file.
virtual void	saveModel (const std::string &fileName)
	Saves the computed model to file.
virtual void	setNparams (unsigned long value)
virtual void	setParam (double value)
virtual void	setProblemType (ProblemType value)
virtual void	setSplitProportion (double value)
virtual void	train (const gMat2D< T > &X, const gMat2D< T > &y)=0
	Initial parameter selection and training.
	~GurlsWrapper ()
	Destructor.
Protected Member Functions
virtual bool	trainedModel ()
	Checks if model has already been trained.
Protected Attributes
std::string	name
	Name of the options structure.
GurlsOptionsList *	opt
	Options structure where information about initial training is stored.
ProblemType	probType
	Problem type.

---

Detailed Description

template<typename T>
class gurls::GurlsWrapper< T >

Definition at line 57 of file wrapper.h.

---

Constructor & Destructor Documentation

template<typename T >

gurls::GurlsWrapper< T >::GurlsWrapper

(

const std::string &

name

)

Parameters:

name	Name of the options structure that will be initialized

Definition at line 10 of file wrapper.hpp.

                                                  :opt(NULL), name(name)
{
    opt = new GurlsOptionsList(name, true);

    setSplitProportion(0.2);
    setNparams(20);
    setProblemType(CLASSIFICATION);
}

---

Member Function Documentation

template<typename T >

T gurls::GurlsWrapper< T >::eval	(	const gVec< T > &	X,
		unsigned long *	index = NULL
	)		[virtual]

Parameters:

[in]	X	Input point
[out]	index	Index of the estimated label

Returns:

Estimated label

Definition at line 26 of file wrapper.hpp.

{
    if(!trainedModel())
        throw gException("Error, Train Model First");

    gMat2D<T>X_mat(1, X.getSize());
    copy(X_mat.getData(), X.getData(), X.getSize());

    gMat2D<T>* pred_mat = eval(X_mat);

    const T* pred = pred_mat->getData();
    const unsigned long size = pred_mat->getSize();

    const T* max = std::max_element(pred, pred+size);
    T ret = *max;
    if(index != NULL)
        *index = max-pred;

    delete pred_mat;
    return ret;
}

template<typename T >

virtual gMat2D<T>* gurls::GurlsWrapper< T >::eval

(

const gMat2D< T > &

X

)

[pure virtual]

Parameters:

[in]

X

Input matrix

Returns:

Matrix of predicted labels

Implemented in gurls::RecursiveRLSWrapper< T >, gurls::NystromWrapper< T >, gurls::RandomFeaturesWrapper< T >, gurls::ICholWrapper< T >, gurls::RLSWrapper< T >, gurls::KernelRLSWrapper< T >, and gurls::GPRWrapper< T >.

template<typename T >

void gurls::GurlsWrapper< T >::loadModel

(

const std::string &

fileName

)

[virtual]

Parameters:

fileName

name of the file containing the data to load

Definition at line 61 of file wrapper.hpp.

{
    opt->load(fileName);
}

template<typename T >

void gurls::GurlsWrapper< T >::saveModel

(

const std::string &

fileName

)

[virtual]

Parameters:

fileName

name of the file where data will be saved

Definition at line 55 of file wrapper.hpp.

{
    opt->save(fileName);
}

template<typename T >

void gurls::GurlsWrapper< T >::setNparams

(

unsigned long

value

)

[virtual]

Parameters:

[in]

value

Definition at line 67 of file wrapper.hpp.

{
    opt->getOptValue<OptNumber>("nlambda") = value;

    if(opt->hasOpt("paramsel.lambdas") && value > 1.0)
    {
        std::cout << "Warning: ignoring previous values of the regularization parameter" << std::endl;
        opt->getOptAs<GurlsOptionsList>("paramsel")->removeOpt("lambdas");
    }
}

template<typename T >

void gurls::GurlsWrapper< T >::setParam

(

double

value

)

[virtual]

Parameters:

[in]

value

Reimplemented in gurls::NystromWrapper< T >.

Definition at line 79 of file wrapper.hpp.

{
    if(!opt->hasOpt("paramsel"))
        opt->addOpt("paramsel", new GurlsOptionsList("paramsel"));

    if(opt->hasOpt("paramsel.lambdas"))
        opt->getOptValue<OptMatrix<gMat2D<T> > >("paramsel.lambdas").getData()[0] = (T)value;
    else
    {
        gMat2D<T> * lambdas = new gMat2D<T>(1,1);
        lambdas->getData()[0] = (T)value;
        opt->getOptAs<GurlsOptionsList>("paramsel")->addOpt("lambdas", new OptMatrix<gMat2D<T> >(*lambdas));
    }

    setNparams(1);
}

template<typename T >

void gurls::GurlsWrapper< T >::setProblemType

(

typename GurlsWrapper< T >::ProblemType

value

)

[virtual]

Parameters:

[in]

value

Definition at line 103 of file wrapper.hpp.

{
    probType = value;

    opt->getOptValue<OptString>("hoperf") = (value == CLASSIFICATION)? "macroavg": "rmse";
}

template<typename T >

void gurls::GurlsWrapper< T >::setSplitProportion

(

double

value

)

[virtual]

Parameters:

[in]

value

Definition at line 97 of file wrapper.hpp.

{
    opt->getOptValue<OptNumber>("hoproportion") = value;
}

template<typename T >

virtual void gurls::GurlsWrapper< T >::train	(	const gMat2D< T > &	X,
		const gMat2D< T > &	y
	)		[pure virtual]

Parameters:

[in]	X	Input data matrix
[in]	Y	Labels matrix

Implemented in gurls::KernelWrapper< T >, gurls::RandomFeaturesWrapper< T >, gurls::RecursiveRLSWrapper< T >, gurls::NystromWrapper< T >, gurls::RLSWrapper< T >, gurls::KernelRLSWrapper< T >, gurls::ICholWrapper< T >, and gurls::GPRWrapper< T >.

template<typename T >

bool gurls::GurlsWrapper< T >::trainedModel

(

)

[protected, virtual]

Parameters:

value
value

Definition at line 111 of file wrapper.hpp.

{
    return opt->hasOpt("optimizer");
}

---

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

• wrapper.h
• wrapper.hpp