#include <Svm.h>
Inheritance diagram for Impala::Core::Training::Svm:
Public Member Functions | |
Svm () | |
virtual | ~Svm () |
virtual void | Train (Util::PropertySet *properties, TrainDataSrc *data) |
virtual Table::ScoreTable * | Predict (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_model * | GetModel () |
bool | Equals (const Svm *other) const |
Private Member Functions | |
double | PredictSingle (const svm_node *problem) |
void | SetModel (svm_model *model) |
Private Attributes | |
svm_model * | mModel |
bool | mIsProbabilityModel |
int | mProbilityIndex |
ILOG_VAR_DEC |
parameters for the model: {w1, w2, C, gamma, cache, degree, coef0, nu, eps, p, shrinking, probability}
Definition at line 49 of file Svm.h.