1 #if !defined(_MODELPARAMOLDSVM_) 2 #define _MODELPARAMOLDSVM_ 20 #ifndef _BINARYCLASSPARMS_
59 const svm_parameter& _param,
90 virtual double C_Param ()
const;
92 virtual double C_Param (MLClassPtr class1,
96 virtual double Gamma ()
const;
104 virtual const svm_parameter&
Param ()
const;
113 virtual void A_Param (
float _A);
114 virtual void C_Param (
double _CC);
116 virtual void C_Param (MLClassPtr class1,
123 virtual void Gamma (
double _gamma);
140 const svm_parameter& _param,
173 void ParseCmdLineParameter (
const KKStr& parameter,
virtual const svm_parameter & Param() const
BinaryClassParmsPtr GetBinaryClassParms(MLClassPtr class1, MLClassPtr class2) const
const BinaryClassParmsListPtr BinaryParmsList() const
virtual void KernalType(SVM_KernalType _kernalType)
virtual void Gamma_Param(double _gamma)
decision_function svm_train_one(const svm_problem *prob, const svm_parameter *param, double Cp, double Cn, std::set< kkint32 > &BSVIndex)
Keeps track of selected features.
ModelParam derived classes will implement their "XmlElement" helper class via this template...
virtual void Gamma(double _gamma)
virtual void ReadXML(XmlStream &s, XmlTagConstPtr tag, VolConstBool &cancelFlag, RunLog &log)
virtual void EncodingMethod(SVM_EncodingMethod _encodingMethod)
virtual void C_Param(double _CC)
KKStr SvmParamToString(const svm_parameter &_param) const
Convert a svm_parameter struct to a cmdline str.
virtual bool UseProbabilityToBreakTies() const
virtual SVM_MachineType MachineType() const
virtual void C_Param(MLClassPtr class1, MLClassPtr class2, double cParam)
virtual void A_Param(float _A)
void SetBinaryClassFields(MLClassPtr class1, MLClassPtr class2, const svm_parameter &_param, FeatureNumListConstPtr _features, float _weight)
virtual SVM_KernalType KernalType() const
virtual kkint32 NumOfFeaturesAfterEncoding(FileDescPtr fileDesc, RunLog &log) const
FeatureNumListConstPtr GetFeatureNums(FileDescPtr fileDesc, MLClassPtr class1, MLClassPtr class2) const
virtual ModelParamTypes ModelParamType() const
ModelParamOldSVM * ModelParamOldSVMPtr
void AddBinaryClassParms(MLClassPtr class1, MLClassPtr class2, const svm_parameter &_param, FeatureNumListConstPtr _selectedFeatures, float _weight)
Add a Binary parameters using svm_parametr cmd line str. Typically used by TrainingConfiguration.
void SetFeatureNums(MLClassPtr class1, MLClassPtr class2, FeatureNumListConstPtr _features, float _weight=-1)
virtual SVM_SelectionMethod SelectionMethod() const
XmlTag const * XmlTagConstPtr
Manages the reading and writing of objects in a simple XML format. For a class to be supported by Xml...
ModelParamOldSVM(const ModelParamOldSVM &_param)
static KKStr Concat(const std::vector< std::string > &values)
Concatenates the list of 'std::string' strings.
virtual void SamplingRate(float _samplingRate)
ModelParamOldSVM * ModelParamOldSVMPtr
KKStr ToCmdLineStr() const
Convert all parameters to a command line string.
virtual void SelectionMethod(SVM_SelectionMethod _selectionMethod)
virtual ModelParamOldSVMPtr Duplicate() const
XmlElementModelParamOldSVM * XmlElementModelParamOldSVMPtr
virtual double Gamma() const
virtual void MachineType(SVM_MachineType _machineType)
virtual void EncodingMethod(EncodingMethodType _encodingMethod)
virtual void SelectedFeatures(const FeatureNumList &_selectedFeatures)
FeatureNumListConst * FeatureNumListConstPtr
virtual float A_Param() const
Used for logging messages.
void EncodeProblem(const struct svm_paramater ¶m, struct svm_problem &prob_in, struct svm_problem &prob_out)
virtual void WriteXML(const KKStr &varName, std::ostream &o) const
virtual double C_Param(MLClassPtr class1, MLClassPtr class2) const
XmlElementModelParamTemplate< ModelParamOldSVM > XmlElementModelParamOldSVM
EncodingMethodType SVM_EncodingMethodToModelParamEncodingMethodType(SVM_EncodingMethod _encodingMethod)
converts Encoding variables from "SVM_EncodingMethod" to "ModelParam::EncodingMethodType" ...
void ParseCmdLine(KKStr _cmdLineStr, bool &_validFormat, RunLog &_log)
virtual float SamplingRate() const
virtual FeatureNumListConstPtr SelectedFeatures() const
Abstract Base class for Machine Learning parameters.
virtual double C_Param() const
virtual ~ModelParamOldSVM()
void AddBinaryClassParms(BinaryClassParmsPtr binaryClassParms)
virtual SVMparamPtr SvmParameters() const
BinaryClassParmsPtr GetParamtersToUseFor2ClassCombo(MLClassPtr class1, MLClassPtr class2)
volatile const bool VolConstBool
virtual float AvgMumOfFeatures(FileDescPtr fileDesc)