npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim > Class Template Reference

#include <LocalLogisticRegression.hh>

Inheritance diagram for npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >:

Public Member Functions
	LogisticRegressionOnGrid (const ArrayND< Numeric, StackLen, StackDim > &numerator, const ArrayND< Numeric, StackLen, StackDim > &denominator, const QuadraticOrthoPolyND &poly, bool calculateLikelihoodGradient)
const ArrayND< Numeric, StackLen, StackDim > &	getNumerator () const
const ArrayND< Numeric, StackLen, StackDim > &	getDenominator () const
virtual void	clear ()
virtual double	result ()
virtual void	process (const unsigned *index, unsigned indexLen, unsigned long linearIndex, const Numeric &value)
Public Member Functions inherited from npstat::LogisticRegressionBase< int >
	LogisticRegressionBase (const QuadraticOrthoPolyND &poly, bool calculateLikelihoodGradient)
unsigned	dim () const
const QuadraticOrthoPolyND &	getPoly () const
bool	calculatingGradient () const
const std::vector< double > &	lastCoeffs () const
void	getGradient (double *buffer, unsigned bufLen) const
double	getPassCount () const
double	getFailCount () const
void	setRegressionBox (const BoxND< int > &box)
void	setLinearMapping (const double *location, const double *scale, unsigned locationAndScaleArraySize)
double	calculateLogLikelihood (const double *coeffs, unsigned nCoeffs)

Additional Inherited Members
Protected Member Functions inherited from npstat::LogisticRegressionBase< int >
void	resetAccumulators ()
Protected Attributes inherited from npstat::LogisticRegressionBase< int >
const QuadraticOrthoPolyND &	poly_
BoxND< int >	regressionBox_
std::vector< double >	location_
std::vector< double >	scale_
std::vector< double >	coords_
std::vector< double >	coeffs_
std::vector< double >	gradBuffer_
std::vector< long double >	gradient_
long double	logli_
long double	passCount_
long double	failCount_
const double	minlog_
const double	maxlog_
const unsigned	mydim_
const bool	calcGradient_

Detailed Description

template<typename Numeric, unsigned StackLen = 1U, unsigned StackDim = 10U>
class npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >

Logistic regression on regularly sampled data

Constructor & Destructor Documentation

LogisticRegressionOnGrid()

template<typename Numeric , unsigned StackLen = 1U, unsigned StackDim = 10U>

npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >::LogisticRegressionOnGrid	(	const ArrayND< Numeric, StackLen, StackDim > &	numerator,
		const ArrayND< Numeric, StackLen, StackDim > &	denominator,
		const QuadraticOrthoPolyND &	poly,
		bool	calculateLikelihoodGradient
	)

Constructor arguments are as follows:

numerator – count of points which "pass" for this grid cell

denominator – count of all points associated with this grid cell

poly – the set of orthogonal polynomial used to construct the local regression surface.

calculateLikelihoodGradient – flag which tells whether the code should calculate the gradient of log-likelihood with respect to coefficients of the local polynomial.

This object will not own "numerator", "denominator", or "poly" objects. These objects must still exist when the LogisticRegressionOnGrid object is in use.

The "standard" situation here is that the regression box is simply taken to be an integer-sized box whose length is the same as the number of steps used to build the polynomials.

Member Function Documentation

clear()

template<typename Numeric , unsigned StackLen = 1U, unsigned StackDim = 10U>

virtual void npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >::clear ( )

inlinevirtual

Method from AbsArrayProjector we have to implement

Implements npstat::AbsArrayProjector< Numeric, double >.

getNumerator()

template<typename Numeric , unsigned StackLen = 1U, unsigned StackDim = 10U>

const ArrayND<Numeric,StackLen,StackDim>& npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >::getNumerator ( ) const

inline

Inspect object properties

process()

template<typename Numeric , unsigned StackLen = 1U, unsigned StackDim = 10U>

virtual void npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >::process ( const unsigned *  index, unsigned  indexLen, unsigned long  linearIndex, const Numeric &  value  )

virtual

Process one array point

Implements npstat::AbsArrayProjector< Numeric, double >.

result()

template<typename Numeric , unsigned StackLen = 1U, unsigned StackDim = 10U>

virtual double npstat::LogisticRegressionOnGrid< Numeric, StackLen, StackDim >::result ( )

inlinevirtual

Return the result at the end of array processing

Implements npstat::AbsArrayProjector< Numeric, double >.

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

• stat/LocalLogisticRegression.hh