general.h File Reference

#include <iostream>

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Defines
#define	DEBUGON
#define	LAMBDA_PREC   1.0E-5
#define	PREC_ARITM   1.0E-7
#define	TNNearlyZero   1E-05
#define	Real   double
#define	JacobiTolerance   1.0e-6
#define	MaxIterations   50
#define	MAXREAL   1.0e+100
#define	MINREAL   -1.0e+100
#define	BLKSIZE   4096
#define	BIG_NR   1000000
#define	SMALL_POZ_VALUE   3.0E-13
#define	LARGE_POZ_VALUE   3.0E+100
#define	MAX_CATEGORIES   10000
#define	MAX_VARIABLES   1000
#define	INT_MAX   2147483647
#define	EBADDIM   1
#define	NonEqual(X, Y)   ( (fabs(X)+fabs(Y))==0.0?0:NonZero((X-Y)/(fabs(X)+fabs(Y))) )
#define	IsEqual(X, Y)   ( (fabs(X)+fabs(Y))==0.0?1:IsZero((X-Y)/(fabs(X)+fabs(Y))) )
#define	NonZero(X)   ( ( (X)>TNNearlyZero ) || ( (X)<-TNNearlyZero ) )
#define	IsZero(X)   ( ( (X)<TNNearlyZero ) && ( (X)>-TNNearlyZero ) )
#define	NonZeroM(X)   ( ( (X)>TNNearlyZero*100 ) || ( (X)<-TNNearlyZero*100 ) )
#define	RANDOM01FLOAT   ( (1.0*rand())/RAND_MAX )
#define	ExitIf(Cond, Text)
#define	ExitIf(Cond, Text)
Functions
double	pow2 (double x)

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Define Documentation

#define BIG_NR   1000000

Definition at line 61 of file general.h. Referenced by CLUS::StreamDCTrainingData::StreamDCTrainingData(), and CLUS::StreamDataProducer::Tick().

#define BLKSIZE   4096

Definition at line 60 of file general.h.

#define DEBUGON

Definition at line 36 of file general.h.

#define EBADDIM   1

Definition at line 72 of file general.h.

#define ExitIf (  Cond, Text   )

Definition at line 89 of file general.h.

#define ExitIf (  Cond, Text   )

Value: if ( Cond ) { \ cout << Text << endl; \ exit(1); \ } Definition at line 89 of file general.h. Referenced by CLUS::MultiDimNormal::ComputeCCoef(), CLUS::CreateStreamDCTrainingDataFromFile(), CLUS::MultiDecisionTree< T_Splitter >::Identify(), CLUS::TrainingData::Normalize(), CLUS::RPMSConsumer::SetRealInput(), and CLUS::StreamDCTrainingData::StreamDCTrainingData().

#define INT_MAX   2147483647

Definition at line 68 of file general.h. Referenced by CLUS::BinaryProbabilisticRegressionTree< T_Distribution, T_Regressor, T_Splitter >::BinaryProbabilisticRegressionTree(), and CLUS::BinaryRegressionTree< T_Distribution, T_Regressor, T_Splitter >::BinaryRegressionTree().

#define IsEqual (  X, Y   )     ( (fabs(X)+fabs(Y))==0.0?1:IsZero((X-Y)/(fabs(X)+fabs(Y))) )

Definition at line 76 of file general.h. Referenced by CLUS::UnidimensionalQDAVariance().

#define IsZero (  X   )     ( ( (X)<TNNearlyZero ) && ( (X)>-TNNearlyZero ) )

Definition at line 78 of file general.h. Referenced by CLUS::ComputeSeparatingHyperplane_LDA().

#define JacobiTolerance   1.0e-6

Definition at line 56 of file general.h.

#define LAMBDA_PREC   1.0E-5

Definition at line 52 of file general.h.

#define LARGE_POZ_VALUE   3.0E+100

Definition at line 63 of file general.h. Referenced by CLUS::UnidimensionalQDAVariance().

#define MAX_CATEGORIES   10000

Definition at line 64 of file general.h. Referenced by CLUS::DiscreteGiniGain().

#define MAX_VARIABLES   1000

Definition at line 65 of file general.h. Referenced by CLUS::BinaryRegressionTree< T_Distribution, T_Regressor, T_Splitter >::Infer(), CLUS::BinaryProbabilisticRegressionTree< T_Distribution, T_Regressor, T_Splitter >::Infer(), CLUS::MultiDecisionTree< T_Splitter >::Infer(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer(), CLUS::BinaryDecisionTree< T_Splitter >::Infer(), CLUS::BinaryRegressionTree< T_Distribution, T_Regressor, T_Splitter >::Prune(), CLUS::BinaryProbabilisticRegressionTree< T_Distribution, T_Regressor, T_Splitter >::Prune(), and CLUS::MultiDecisionTree< T_Splitter >::Prune().

#define MaxIterations   50

Definition at line 57 of file general.h.

#define MAXREAL   1.0e+100

Definition at line 58 of file general.h. Referenced by CLUS::MultiDimNormal::LearnProbability().

#define MINREAL   -1.0e+100

Definition at line 59 of file general.h.

#define NonEqual (  X, Y   )     ( (fabs(X)+fabs(Y))==0.0?0:NonZero((X-Y)/(fabs(X)+fabs(Y))) )

Definition at line 75 of file general.h. Referenced by CLUS::DiscreteGiniGain(), and CLUS::UnidimensionalQDA().

#define NonZero (  X   )     ( ( (X)>TNNearlyZero ) || ( (X)<-TNNearlyZero ) )

Definition at line 77 of file general.h. Referenced by CLUS::MultiDecisionTreeNode< T_Splitter >::combineCenters(), CLUS::MultiDecisionTreeNode< T_Splitter >::combineLabeledCenters(), CLUS::MultiDecisionTree< T_Splitter >::Identify(), and CLUS::UnidimensionalQDA().

#define NonZeroM (  X   )     ( ( (X)>TNNearlyZero*100 ) || ( (X)<-TNNearlyZero*100 ) )

Definition at line 79 of file general.h.

#define PREC_ARITM   1.0E-7

Definition at line 53 of file general.h.

#define RANDOM01FLOAT   ( (1.0*rand())/RAND_MAX )

Definition at line 81 of file general.h. Referenced by CLUS::GenerateRandomVector2(), CLUS::SphericCluster::InitializeOnPoint(), CLUS::SphericCluster::RandomCluster(), CLUS::SimpleNormalDistribution::RandomDistribution(), and CLUS::MultiDimNormal::RandomDistribution().

#define Real   double

Definition at line 55 of file general.h.

#define SMALL_POZ_VALUE   3.0E-13

Definition at line 62 of file general.h. Referenced by CLUS::MultiDimNormal::ComputeCCoef(), CLUS::ComputeSeparatingHyperplane_QDA(), CLUS::UnidimensionalQDA(), CLUS::UnidimensionalQDAVariance(), CLUS::MultidimNormalStatistics::UpdateParameters(), and CLUS::MultiDimNormal::UpdateParameters().

#define TNNearlyZero   1E-05

Definition at line 54 of file general.h. Referenced by CLUS::ComputeSeparatingHyperplane_LDA(), and CLUS::BinaryObliqueSplitter::ComputeSplitVariable().

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Function Documentation

double pow2 (  double  x  )  [inline]

Definition at line 93 of file general.h. Referenced by CLUS::NormalStatistics::AddStatisticsShifted(), CLUS::NormalStatistics::AddWeightedStatistics(), CLUS::SphericCluster::AdjustPrototypes(), CLUS::HiperPlanCluster::AdjustPrototypes(), CLUS::BinaryGiniGain(), CLUS::SphericCluster::ClusDistance(), CLUS::HiperPlanCluster::ClusDistance(), CLUS::MultiDimNormal::ComputeCCoef(), CLUS::NormalStatistics::ComputeGiniGain(), CLUS::ComputeSeparatingHyperplane_Anova(), CLUS::ComputeSeparatingHyperplane_QDA(), CLUS::SphericCluster::CorrectAppartGrade(), CLUS::HiperPlanCluster::CorrectAppartGrade(), CLUS::NormalStatistics::CorrectWeightedStatistics(), CLUS::EMHiperPlan::EMHiperPlan(), CLUS::NormalStatistics::getLCVariance(), CLUS::RPMSConsumer::GetNRMSE(), CLUS::NormalStatistics::getVariance(), CLUS::SphericCluster::InferDistance(), CLUS::HiperPlanCluster::InferDistance(), CLUS::MultiDimNormal::InferProbability(), CLUS::SimpleNormalDistribution::LearnProbability(), CLUS::MultiDimNormal::LearnProbability(), CLUS::EMHiperPlan::LoadFromStream(), CLUS::MultidimNormalStatistics::MaxGini(), CLUS::TrainingData::Normalize(), CLUS::PValueNormalDistribution(), CLUS::MultiDimNormal::RandomDistribution(), CLUS::Scale::SetCoefForInput(), CLUS::Scale::SetCoefForOutput(), CLUS::SetNormTo(), CLUS::EMHiperPlan::SetOptionDbl(), CLUS::EMHiperPlan::SetSigma(), CLUS::SimpleNormalDistribution::SimpleNormalDistribution(), CLUS::SumPow2(), CLUS::RPMSConsumer::Tick(), CLUS::UnidimensionalQDA(), CLUS::UnidimensionalQDAVariance(), CLUS::SimpleNormalDistribution::UpdateParameters(), CLUS::MultiDimNormal::UpdateParameters(), CLUS::BinaryRegressionTreeNode< T_Distribution, T_Regressor, T_Splitter >::UpdatePruningStatistics(), CLUS::BinaryProbabilisticRegressionTreeNode< T_Distribution, T_Regressor, T_Splitter >::UpdatePruningStatistics(), CLUS::BinaryProbabilisticDecisionTreeNode< T_Splitter >::UpdatePruningStatistics(), CLUS::NormalStatistics::UpdateStatistics(), and CLUS::SimpleNormalDistribution::UpdateStatistics().

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