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Impala::Core::Training::Svm Class Reference

SVM is a well known Classifier, see internet for details. More...

#include <Svm.h>

Inheritance diagram for Impala::Core::Training::Svm:

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Collaboration diagram for Impala::Core::Training::Svm:

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List of all members.

Public Member Functions

 Svm ()
virtual ~Svm ()
virtual void Train (Util::PropertySet *properties, TrainDataSrc *data)
virtual Table::ScoreTablePredict (TrainDataSrc *data)
virtual void PredictForActiveLearn (Matrix::DistributedAccess &da, Table::QuidTable *columnQuids, Core::Table::SimilarityTableSet::SimTableType *result)
double Predict (const Impala::Core::Vector::VectorTem< double > *feature)
void LoadModel (const std::string &name, Util::Database *db)
void SaveModel (const std::string &name, Util::Database *db)
void OverrideModelOptions (Util::PropertySet *properties)
const svm_modelGetModel ()
bool Equals (const Svm *other) const

Private Member Functions

double PredictSingle (const svm_node *problem)
void SetModel (svm_model *model)

Private Attributes

svm_modelmModel
bool mIsProbabilityModel
int mProbilityIndex
 ILOG_VAR_DEC

Detailed Description

SVM is a well known Classifier, see internet for details.

Todo:
Fix the machanism to set gamma to 1/vectorlength. See OverrideModelOptions(), Train() and MakeSvmParams().
Warning about libsvm! (Just in case other people ever want to change this part of Impala) Things I (Michiel) learned the hard way:

parameters for the model: {w1, w2, C, gamma, cache, degree, coef0, nu, eps, p, shrinking, probability}

Definition at line 49 of file Svm.h.


The documentation for this class was generated from the following file:
Generated on Fri Mar 19 11:23:55 2010 for ImpalaSrc by  doxygen 1.5.1