FuncLogisticModel.hpp

/*
 * FuncLogisticModel.hpp
 * 
 * Copyright 2018 Fernando Pujaico Rivera <fernando.pujaico.rivera@gmail.com>
 * 
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 * 
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 * 
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
 * MA 02110-1301, USA.
 * 
 */
 
#ifndef __PDS_FUNCLOGISTICMODEL_HPP__
#define __PDS_FUNCLOGISTICMODEL_HPP__
    
#include <string>
#include <list>
#include <Pds/Ra>
#include <Pds/IterationConf>
#include <Pds/DataErrorCurve>
 
namespace Pds{
 
namespace LogisticModel{
 
 
Pds::Vector Classify(const Pds::Vector &W,const Pds::Matrix &X);
 
 
    double CostInformationGain(const Pds::Vector &W,const Pds::Matrix &X,const Pds::Vector &Y);
    
    Pds::Vector GradientCostInformationGain(    const Pds::Vector &W,
                                                const Pds::Matrix &X,
                                                const Pds::Vector &Y,
                                                double h);
    
    
 
    
    double CostCrossEntropy(const Pds::Vector &W,const Pds::Matrix &X,const Pds::Vector &Y);
 
    double CostMeanSquare(const Pds::Vector &W,const Pds::Matrix &X,const Pds::Vector &Y);
 
 
    Pds::Vector GetW0MeanMethod(const Pds::Matrix &X);
    
    Pds::Vector GetW0CornerMeanMethod(const Pds::Matrix &X, double Delta=0.001);
    
    Pds::Vector GetW0MeanSquareMethod(const Pds::Matrix &X);
 
    Pds::Vector FittingLogitMeanSquare(  Pds::IterationConf &Conf,
                                            const Pds::Matrix &X,
                                            const Pds::Vector &Y,
                                            double Delta=0.0001);
 
    Pds::Vector FittingLogitMeanSquare(  const Pds::Matrix &X,
                                            const Pds::Vector &Y,
                                            double Delta=0.0001);
 
 
    Pds::Vector FittingLogitWeightedMeanSquare( Pds::IterationConf &Conf,
                                                const Pds::Matrix &X,
                                                const Pds::Vector &Y,
                                                const Pds::Vector &D,
                                                double Delta=0.0001);
    Pds::Vector FittingLogitWeightedMeanSquare(  const Pds::Matrix &X,
                                            const Pds::Vector &Y,
                                            const Pds::Vector &D,
                                            double Delta=0.0001);
 
 
    Pds::Vector FittingRobustLogitMeanSquare(   const Pds::Matrix &X,
                                                const Pds::Vector &Y,
                                                double Delta=0.0001,
                                                unsigned int N=2,
                                                double Offset=0.1);
    
    Pds::Vector FittingRobustLogitMeanSquare(   Pds::IterationConf &Conf,
                                                const Pds::Matrix &X,
                                                const Pds::Vector &Y,
                                                double Delta=0.0001,
                                                unsigned int N=2,
                                                double Offset=0.1);
    
Pds::Vector FittingKmeansLogitMeanSquare(   Pds::IterationConf &Conf,
                                            const Pds::Matrix &X,
                                            const Pds::Vector &Y,
                                            double Delta);
 
    Pds::Vector FittingGradientCrossEntropy(    Pds::IterationConf &Conf,
                                                const Pds::Matrix &X,
                                                const Pds::Vector &Y,
                                                const Pds::Vector &W0);
 
    Pds::Vector FittingGradientSVM( Pds::IterationConf &Conf,
                                    const Pds::Matrix &X,
                                    const Pds::Vector &Y,
                                    const Pds::Vector &W0);
 
    Pds::Vector FittingOrtogonalIG( const Pds::Matrix &X,
                                    const Pds::Vector &Y,
                                    unsigned int MinID);
                                
    Pds::Vector FittingGradientIG(  Pds::IterationConf &Conf,
                                    const Pds::Matrix &X,
                                    const Pds::Vector &Y,
                                    const Pds::Vector &W0);
                                
    Pds::Vector FittingParrallelPlaneIS(const Pds::Matrix &X,
                                        const Pds::Vector &Y,
                                        const Pds::Vector &W0,
                                        double *ISmin=NULL,
                                        double Delta=0.001);
                                        
    Pds::Vector FittingByFactor(const Pds::Matrix &X,
                                const Pds::Vector &Y,
                                const Pds::Vector &W0,
                                double Delta=0.001);
Pds::DataErrorCurve LearningCurves(   Pds::IterationConf &Conf,
                                        const Pds::Matrix &Xtr,
                                        const Pds::Vector &Ytr,
                                        const Pds::Matrix &Xcv,
                                        const Pds::Vector &Ycv,
                                        double percent);
 
 
 
} // namespace Ml
 
} // namespace Pds
 
 
#endif /* __PDS_FUNCLOGISTICMODEL_HPP__ */