Logo ROOT   6.21/01
Reference Guide
TMVA::MethodSVM Class Reference

SMO Platt's SVM classifier with Keerthi & Shavade improvements.

Definition at line 57 of file MethodSVM.h.

Public Member Functions

 MethodSVM (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
 standard constructor More...
 
 MethodSVM (DataSetInfo &theData, const TString &theWeightFile)
 constructor from weight file More...
 
virtual ~MethodSVM (void)
 destructor More...
 
void AddWeightsXMLTo (void *parent) const
 write configuration to xml file More...
 
const RankingCreateRanking ()
 
void GetMGamma (const std::vector< float > &gammas)
 Produces GammaList string for multigaussian kernel to be written to xml file. More...
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 returns MVA value for given event More...
 
const std::vector< Float_t > & GetRegressionValues ()
 
std::map< TString, std::vector< Double_t > > GetTuningOptions ()
 GetTuningOptions Function to allow for ranges and number of steps (for scan) when optimising kernel function parameters. More...
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
 SVM can handle classification with 2 classes and regression with one regression-target. More...
 
void Init (void)
 default initialisation More...
 
std::vector< TMVA::SVKernelFunction::EKernelTypeMakeKernelList (std::string multiKernels, TString kernel)
 MakeKernelList Function providing string manipulation for product or sum of kernels functions to take list of kernels specified in the booking of the method and provide a vector of SV kernels to iterate over in SVKernelFunction. More...
 
virtual std::map< TString, Double_tOptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="Minuit")
 Optimize Tuning Parameters This is used to optimise the kernel function parameters and cost. More...
 
virtual void ReadWeightsFromStream (TFile &)
 
virtual void ReadWeightsFromStream (std::istream &)=0
 
void ReadWeightsFromStream (std::istream &istr)
 
void ReadWeightsFromStream (TFile &fFin)
 TODO write IT. More...
 
void ReadWeightsFromXML (void *wghtnode)
 
void Reset (void)
 
void SetCost (Double_t c)
 
void SetGamma (Double_t g)
 
void SetKappa (Double_t k)
 
void SetMGamma (std::string &mg)
 Takes as input a string of values for multigaussian gammas and splits it, filling the gamma vector required by the SVKernelFunction. More...
 
void SetMult (Double_t m)
 
void SetOrder (Double_t o)
 
void SetTheta (Double_t t)
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 Set the tuning parameters according to the argument. More...
 
void Train (void)
 Train SVM. More...
 
void WriteWeightsToStream (TFile &fout) const
 TODO write IT write training sample (TTree) to file. More...
 
- Public Member Functions inherited from TMVA::MethodBase
 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="")
 standard constructor More...
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...
 
virtual ~MethodBase ()
 destructor More...
 
void AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)
 
TDirectoryBaseDir () const
 returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored More...
 
virtual void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
DataSetData () const
 
DataSetInfoDataInfo () const
 
void DisableWriting (Bool_t setter)
 
Bool_t DoMulticlass () const
 
Bool_t DoRegression () const
 
void ExitFromTraining ()
 
Types::EAnalysisType GetAnalysisType () const
 
UInt_t GetCurrentIter ()
 
virtual Double_t GetEfficiency (const TString &, Types::ETreeType, Double_t &err)
 fill background efficiency (resp. More...
 
const EventGetEvent () const
 
const EventGetEvent (const TMVA::Event *ev) const
 
const EventGetEvent (Long64_t ievt) const
 
const EventGetEvent (Long64_t ievt, Types::ETreeType type) const
 
const std::vector< TMVA::Event * > & GetEventCollection (Types::ETreeType type)
 returns the event collection (i.e. More...
 
TFileGetFile () const
 
const TStringGetInputLabel (Int_t i) const
 
const char * GetInputTitle (Int_t i) const
 
const TStringGetInputVar (Int_t i) const
 
TMultiGraphGetInteractiveTrainingError ()
 
const TStringGetJobName () const
 
virtual Double_t GetKSTrainingVsTest (Char_t SorB, TString opt="X")
 
virtual Double_t GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
 plot significance, \( \frac{S}{\sqrt{S^2 + B^2}} \), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More...
 
UInt_t GetMaxIter ()
 
Double_t GetMean (Int_t ivar) const
 
const TStringGetMethodName () const
 
Types::EMVA GetMethodType () const
 
TString GetMethodTypeName () const
 
virtual TMatrixD GetMulticlassConfusionMatrix (Double_t effB, Types::ETreeType type)
 Construct a confusion matrix for a multiclass classifier. More...
 
virtual std::vector< Float_tGetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual std::vector< Float_tGetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual const std::vector< Float_t > & GetMulticlassValues ()
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=0, Double_t *errUpper=0)
 
const char * GetName () const
 
UInt_t GetNEvents () const
 temporary event when testing on a different DataSet than the own one More...
 
UInt_t GetNTargets () const
 
UInt_t GetNvar () const
 
UInt_t GetNVariables () const
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
const TString GetProbaName () const
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity:

\[ R(x) = \int_{[-\infty..x]} { PDF(x') dx' } \]

where PDF(x) is the PDF of the classifier's signal or background distribution More...

 
virtual void GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const
 
const std::vector< Float_t > & GetRegressionValues (const TMVA::Event *const ev)
 
Double_t GetRMS (Int_t ivar) const
 
virtual Double_t GetROCIntegral (TH1D *histS, TH1D *histB) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetROCIntegral (PDF *pdfS=0, PDF *pdfB=0) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

More...
 
virtual Double_t GetSeparation (PDF *pdfS=0, PDF *pdfB=0) const
 compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

More...
 
Double_t GetSignalReferenceCut () const
 
Double_t GetSignalReferenceCutOrientation () const
 
virtual Double_t GetSignificance () const
 compute significance of mean difference

\[ significance = \frac{|<S> - <B>|}{\sqrt{RMS_{S2} + RMS_{B2}}} \]

More...
 
const EventGetTestingEvent (Long64_t ievt) const
 
Double_t GetTestTime () const
 
const TStringGetTestvarName () const
 
virtual Double_t GetTrainingEfficiency (const TString &)
 
const EventGetTrainingEvent (Long64_t ievt) const
 
virtual const std::vector< Float_t > & GetTrainingHistory (const char *)
 
UInt_t GetTrainingROOTVersionCode () const
 
TString GetTrainingROOTVersionString () const
 calculates the ROOT version string from the training version code on the fly More...
 
UInt_t GetTrainingTMVAVersionCode () const
 
TString GetTrainingTMVAVersionString () const
 calculates the TMVA version string from the training version code on the fly More...
 
Double_t GetTrainTime () const
 
TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true)
 
const TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const
 
TString GetWeightFileName () const
 retrieve weight file name More...
 
Double_t GetXmax (Int_t ivar) const
 
Double_t GetXmin (Int_t ivar) const
 
Bool_t HasMVAPdfs () const
 
void InitIPythonInteractive ()
 
Bool_t IsModelPersistence () const
 
virtual Bool_t IsSignalLike ()
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background More...
 
virtual Bool_t IsSignalLike (Double_t mvaVal)
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would be selected as signal or background More...
 
Bool_t IsSilentFile () const
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored More...
 
void PrintHelpMessage () const
 prints out method-specific help method More...
 
void ProcessSetup ()
 process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void ReadStateFromFile ()
 Function to write options and weights to file. More...
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods More...
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file More...
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory More...
 
void RerouteTransformationHandler (TransformationHandler *fTargetTransformation)
 
virtual void SetAnalysisType (Types::EAnalysisType type)
 
void SetBaseDir (TDirectory *methodDir)
 
void SetFile (TFile *file)
 
void SetMethodBaseDir (TDirectory *methodDir)
 
void SetMethodDir (TDirectory *methodDir)
 
void SetModelPersistence (Bool_t status)
 
void SetSignalReferenceCut (Double_t cut)
 
void SetSignalReferenceCutOrientation (Double_t cutOrientation)
 
void SetSilentFile (Bool_t status)
 
void SetTestTime (Double_t testTime)
 
void SetTestvarName (const TString &v="")
 
void SetTrainTime (Double_t trainTime)
 
void SetupMethod ()
 setup of methods More...
 
virtual void TestClassification ()
 initialization More...
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
bool TrainingEnded ()
 
void TrainMethod ()
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
virtual void WriteMonitoringHistosToFile () const
 write special monitoring histograms to file dummy implementation here --------------— More...
 
void WriteStateToFile () const
 write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created More...
 
- Public Member Functions inherited from TMVA::IMethod
 IMethod ()
 
virtual ~IMethod ()
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 constructor More...
 
virtual ~Configurable ()
 default destructor More...
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file More...
 
template<class T >
void AddPreDefVal (const T &)
 
template<class T >
void AddPreDefVal (const TString &optname, const T &)
 
void CheckForUnusedOptions () const
 checks for unused options in option string More...
 
template<class T >
OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc="")
 
template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc)
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)
 
const char * GetConfigDescription () const
 
const char * GetConfigName () const
 
const TStringGetOptions () const
 
MsgLoggerLog () const
 
virtual void ParseOptions ()
 options parser More...
 
void PrintOptions () const
 prints out the options set in the options string and the defaults More...
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file More...
 
void ReadOptionsFromXML (void *node)
 
void SetConfigDescription (const char *d)
 
void SetConfigName (const char *n)
 
void SetMsgType (EMsgType t)
 
void SetOptions (const TString &s)
 
void WriteOptionsToStream (std::ostream &o, const TString &prefix) const
 write options to output stream (e.g. in writing the MVA weight files More...
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TString &name, const TString &title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor. More...
 
virtual ~TNamed ()
 TNamed destructor. More...
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings (""). More...
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects. More...
 
virtual void Copy (TObject &named) const
 Copy this to obj. More...
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer. More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title. More...
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator. More...
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title. More...
 
virtual void SetName (const char *name)
 Set the name of the TNamed. More...
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title). More...
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed. More...
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject. More...
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor. More...
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
ULong_t CheckedHash ()
 Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad). More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
Bool_t HasInconsistentHash () const
 Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. More...
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
void InvertBit (UInt_t f)
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
void SetBit (UInt_t f)
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
R__ALWAYS_INLINE Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 

Protected Member Functions

void GetHelpMessage () const
 get help message text More...
 
void MakeClassSpecific (std::ostream &, const TString &) const
 write specific classifier response More...
 
- Protected Member Functions inherited from TMVA::MethodBase
const TStringGetInternalVarName (Int_t ivar) const
 
virtual std::vector< Double_tGetMvaValues (Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
 get all the MVA values for the events of the current Data type More...
 
const TStringGetOriginalVarName (Int_t ivar) const
 
const TStringGetWeightFileDir () const
 
Bool_t HasTrainingTree () const
 
Bool_t Help () const
 
Bool_t IgnoreEventsWithNegWeightsInTraining () const
 
Bool_t IsConstructedFromWeightFile () const
 
Bool_t IsNormalised () const
 
virtual void MakeClassSpecificHeader (std::ostream &, const TString &="") const
 
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
void SetNormalised (Bool_t norm)
 
void SetWeightFileDir (TString fileDir)
 set directory of weight file More...
 
void SetWeightFileName (TString)
 set the weight file name (depreciated) More...
 
void Statistics (Types::ETreeType treeType, const TString &theVarName, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &)
 calculates rms,mean, xmin, xmax of the event variable this can be either done for the variables as they are or for normalised variables (in the range of 0-1) if "norm" is set to kTRUE More...
 
Bool_t TxtWeightsOnly () const
 
Bool_t Verbose () const
 
- Protected Member Functions inherited from TMVA::Configurable
void EnableLooseOptions (Bool_t b=kTRUE)
 
const TStringGetReferenceFile () const
 
Bool_t LooseOptionCheckingEnabled () const
 
void ResetSetFlag ()
 resets the IsSet flag for all declare options to be called before options are read from stream More...
 
void WriteOptionsReferenceToFile ()
 write complete options to output stream More...
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 
void MakeZombie ()
 

Private Member Functions

void DeclareCompatibilityOptions ()
 options that are used ONLY for the READER to ensure backward compatibility More...
 
void DeclareOptions ()
 declare options available for this method More...
 
Double_t getLoss (TString lossFunction)
 getLoss Calculates loss for testing dataset. More...
 
void ProcessOptions ()
 option post processing (if necessary) More...
 

Private Attributes

Float_t fBparm
 
Float_t fCost
 
Int_t fDataSize
 
Float_t fDoubleSigmaSquared
 
Float_t fGamma
 
std::string fGammaList
 
std::string fGammas
 
std::vector< TMVA::SVEvent * > * fInputData
 
Float_t fKappa
 
TString fLoss
 
UInt_t fMaxIter
 
TVectorDfMaxVars
 
std::vector< Float_tfmGamma
 
TVectorDfMinVars
 
Float_t fMult
 
std::string fMultiKernels
 
UShort_t fNSubSets
 
Float_t fNumVars
 
Int_t fOrder
 
std::vector< TMVA::SVEvent * > * fSupportVectors
 
SVKernelFunctionfSVKernelFunction
 
TString fTheKernel
 
Float_t fTheta
 
Float_t fTolerance
 
std::string fTune
 
std::vector< TStringfVarNames
 
SVWorkingSetfWgSet
 

Additional Inherited Members

- Public Types inherited from TMVA::MethodBase
enum  EWeightFileType { kROOT =0, kTEXT }
 
- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5),
  kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 
- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 
- Public Attributes inherited from TMVA::MethodBase
Bool_t fSetupCompleted
 
const EventfTmpEvent
 
TrainingHistory fTrainHistory
 
- Protected Attributes inherited from TMVA::MethodBase
Types::EAnalysisType fAnalysisType
 
UInt_t fBackgroundClass
 
bool fExitFromTraining = false
 
std::vector< TString > * fInputVars
 
IPythonInteractivefInteractive = nullptr
 
UInt_t fIPyCurrentIter = 0
 
UInt_t fIPyMaxIter = 0
 
std::vector< Float_t > * fMulticlassReturnVal
 
Int_t fNbins
 
Int_t fNbinsH
 
Int_t fNbinsMVAoutput
 
RankingfRanking
 
std::vector< Float_t > * fRegressionReturnVal
 
ResultsfResults
 
UInt_t fSignalClass
 
- Protected Attributes inherited from TMVA::Configurable
MsgLoggerfLogger
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

#include <TMVA/MethodSVM.h>

Inheritance diagram for TMVA::MethodSVM:
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Constructor & Destructor Documentation

◆ MethodSVM() [1/2]

TMVA::MethodSVM::MethodSVM ( const TString jobName,
const TString methodTitle,
DataSetInfo theData,
const TString theOption = "" 
)

standard constructor

Definition at line 90 of file MethodSVM.cxx.

◆ MethodSVM() [2/2]

TMVA::MethodSVM::MethodSVM ( DataSetInfo theData,
const TString theWeightFile 
)

constructor from weight file

Definition at line 126 of file MethodSVM.cxx.

◆ ~MethodSVM()

TMVA::MethodSVM::~MethodSVM ( void  )
virtual

destructor

Definition at line 161 of file MethodSVM.cxx.

Member Function Documentation

◆ AddWeightsXMLTo()

void TMVA::MethodSVM::AddWeightsXMLTo ( void parent) const
virtual

write configuration to xml file

Implements TMVA::MethodBase.

Definition at line 398 of file MethodSVM.cxx.

◆ CreateRanking()

const Ranking* TMVA::MethodSVM::CreateRanking ( )
inlinevirtual

Implements TMVA::MethodBase.

Definition at line 100 of file MethodSVM.h.

◆ DeclareCompatibilityOptions()

void TMVA::MethodSVM::DeclareCompatibilityOptions ( )
privatevirtual

options that are used ONLY for the READER to ensure backward compatibility

Reimplemented from TMVA::MethodBase.

Definition at line 251 of file MethodSVM.cxx.

◆ DeclareOptions()

void TMVA::MethodSVM::DeclareOptions ( )
privatevirtual

declare options available for this method

Implements TMVA::MethodBase.

Definition at line 220 of file MethodSVM.cxx.

◆ GetHelpMessage()

void TMVA::MethodSVM::GetHelpMessage ( ) const
protectedvirtual

get help message text

typical length of text line: "|--------------------------------------------------------------|"

Implements TMVA::IMethod.

Definition at line 715 of file MethodSVM.cxx.

◆ getLoss()

Double_t TMVA::MethodSVM::getLoss ( TString  lossFunction)
private

getLoss Calculates loss for testing dataset.

The loss function can be specified when booking the method, otherwise defaults to hinge loss. Currently not used however is accesible if required.

Definition at line 1163 of file MethodSVM.cxx.

◆ GetMGamma()

void TMVA::MethodSVM::GetMGamma ( const std::vector< float > &  gammas)

Produces GammaList string for multigaussian kernel to be written to xml file.

Definition at line 1032 of file MethodSVM.cxx.

◆ GetMvaValue()

Double_t TMVA::MethodSVM::GetMvaValue ( Double_t err = 0,
Double_t errUpper = 0 
)
virtual

returns MVA value for given event

Implements TMVA::MethodBase.

Definition at line 577 of file MethodSVM.cxx.

◆ GetRegressionValues()

const std::vector< Float_t > & TMVA::MethodSVM::GetRegressionValues ( )
virtual

Reimplemented from TMVA::MethodBase.

Definition at line 602 of file MethodSVM.cxx.

◆ GetTuningOptions()

std::map< TString, std::vector< Double_t > > TMVA::MethodSVM::GetTuningOptions ( )

GetTuningOptions Function to allow for ranges and number of steps (for scan) when optimising kernel function parameters.

Specified when booking the method after the parameter to be optimised between square brackets with each value separated by ;, the first value is the lower limit, the second the upper limit and the third is the number of steps. Example: "Tune=Gamma[0.01;1.0;100]" would only tune the RBF Gamma between 0.01 and 100 steps.

Definition at line 1106 of file MethodSVM.cxx.

◆ HasAnalysisType()

Bool_t TMVA::MethodSVM::HasAnalysisType ( Types::EAnalysisType  type,
UInt_t  numberClasses,
UInt_t  numberTargets 
)
virtual

SVM can handle classification with 2 classes and regression with one regression-target.

Implements TMVA::IMethod.

Definition at line 195 of file MethodSVM.cxx.

◆ Init()

void TMVA::MethodSVM::Init ( void  )
virtual

default initialisation

Implements TMVA::MethodBase.

Definition at line 205 of file MethodSVM.cxx.

◆ MakeClassSpecific()

void TMVA::MethodSVM::MakeClassSpecific ( std::ostream &  fout,
const TString className 
) const
protectedvirtual

write specific classifier response

Reimplemented from TMVA::MethodBase.

Definition at line 635 of file MethodSVM.cxx.

◆ MakeKernelList()

std::vector< TMVA::SVKernelFunction::EKernelType > TMVA::MethodSVM::MakeKernelList ( std::string  multiKernels,
TString  kernel 
)

MakeKernelList Function providing string manipulation for product or sum of kernels functions to take list of kernels specified in the booking of the method and provide a vector of SV kernels to iterate over in SVKernelFunction.

Example:

"KernelList=RBF*Polynomial" would use a product of the RBF and Polynomial kernels.

Definition at line 1054 of file MethodSVM.cxx.

◆ OptimizeTuningParameters()

std::map< TString, Double_t > TMVA::MethodSVM::OptimizeTuningParameters ( TString  fomType = "ROCIntegral",
TString  fitType = "Minuit" 
)
virtual

Optimize Tuning Parameters This is used to optimise the kernel function parameters and cost.

All kernel parameters are optimised by default with default ranges, however the parameters to be optimised can be set when booking the method with the option Tune.

Example:

"Tune=Gamma[0.01;1.0;100]" would only tune the RBF Gamma between 0.01 and 1.0 with 100 steps.

Reimplemented from TMVA::MethodBase.

Definition at line 760 of file MethodSVM.cxx.

◆ ProcessOptions()

void TMVA::MethodSVM::ProcessOptions ( )
privatevirtual

option post processing (if necessary)

Implements TMVA::MethodBase.

Definition at line 268 of file MethodSVM.cxx.

◆ ReadWeightsFromStream() [1/4]

virtual void TMVA::MethodBase::ReadWeightsFromStream
inline

Definition at line 265 of file MethodBase.h.

◆ ReadWeightsFromStream() [2/4]

virtual void TMVA::MethodBase::ReadWeightsFromStream

◆ ReadWeightsFromStream() [3/4]

void TMVA::MethodSVM::ReadWeightsFromStream ( std::istream &  istr)
virtual

Implements TMVA::MethodBase.

Definition at line 513 of file MethodSVM.cxx.

◆ ReadWeightsFromStream() [4/4]

void TMVA::MethodSVM::ReadWeightsFromStream ( TFile fFin)
virtual

TODO write IT.

Reimplemented from TMVA::MethodBase.

Definition at line 570 of file MethodSVM.cxx.

◆ ReadWeightsFromXML()

void TMVA::MethodSVM::ReadWeightsFromXML ( void wghtnode)
virtual

Implements TMVA::MethodBase.

Definition at line 430 of file MethodSVM.cxx.

◆ Reset()

void TMVA::MethodSVM::Reset ( void  )
virtual

Reimplemented from TMVA::MethodBase.

Definition at line 174 of file MethodSVM.cxx.

◆ SetCost()

void TMVA::MethodSVM::SetCost ( Double_t  c)
inline

Definition at line 104 of file MethodSVM.h.

◆ SetGamma()

void TMVA::MethodSVM::SetGamma ( Double_t  g)
inline

Definition at line 103 of file MethodSVM.h.

◆ SetKappa()

void TMVA::MethodSVM::SetKappa ( Double_t  k)
inline

Definition at line 108 of file MethodSVM.h.

◆ SetMGamma()

void TMVA::MethodSVM::SetMGamma ( std::string &  mg)

Takes as input a string of values for multigaussian gammas and splits it, filling the gamma vector required by the SVKernelFunction.

Example: "GammaList=0.1,0.2,0.3" would make a vector with Gammas of 0.1,0.2 & 0.3 corresponding to input variables 1,2 & 3 respectively.

Definition at line 1018 of file MethodSVM.cxx.

◆ SetMult()

void TMVA::MethodSVM::SetMult ( Double_t  m)
inline

Definition at line 109 of file MethodSVM.h.

◆ SetOrder()

void TMVA::MethodSVM::SetOrder ( Double_t  o)
inline

Definition at line 106 of file MethodSVM.h.

◆ SetTheta()

void TMVA::MethodSVM::SetTheta ( Double_t  t)
inline

Definition at line 107 of file MethodSVM.h.

◆ SetTuneParameters()

void TMVA::MethodSVM::SetTuneParameters ( std::map< TString, Double_t tuneParameters)
virtual

Set the tuning parameters according to the argument.

Reimplemented from TMVA::MethodBase.

Definition at line 917 of file MethodSVM.cxx.

◆ Train()

void TMVA::MethodSVM::Train ( void  )
virtual

Train SVM.

Implements TMVA::MethodBase.

Definition at line 281 of file MethodSVM.cxx.

◆ WriteWeightsToStream()

void TMVA::MethodSVM::WriteWeightsToStream ( TFile fout) const

TODO write IT write training sample (TTree) to file.

Definition at line 507 of file MethodSVM.cxx.

Member Data Documentation

◆ fBparm

Float_t TMVA::MethodSVM::fBparm
private

Definition at line 133 of file MethodSVM.h.

◆ fCost

Float_t TMVA::MethodSVM::fCost
private

Definition at line 129 of file MethodSVM.h.

◆ fDataSize

Int_t TMVA::MethodSVM::fDataSize
private

Definition at line 158 of file MethodSVM.h.

◆ fDoubleSigmaSquared

Float_t TMVA::MethodSVM::fDoubleSigmaSquared
private

Definition at line 145 of file MethodSVM.h.

◆ fGamma

Float_t TMVA::MethodSVM::fGamma
private

Definition at line 134 of file MethodSVM.h.

◆ fGammaList

std::string TMVA::MethodSVM::fGammaList
private

Definition at line 154 of file MethodSVM.h.

◆ fGammas

std::string TMVA::MethodSVM::fGammas
private

Definition at line 153 of file MethodSVM.h.

◆ fInputData

std::vector<TMVA::SVEvent*>* TMVA::MethodSVM::fInputData
private

Definition at line 136 of file MethodSVM.h.

◆ fKappa

Float_t TMVA::MethodSVM::fKappa
private

Definition at line 148 of file MethodSVM.h.

◆ fLoss

TString TMVA::MethodSVM::fLoss
private

Definition at line 159 of file MethodSVM.h.

◆ fMaxIter

UInt_t TMVA::MethodSVM::fMaxIter
private

Definition at line 131 of file MethodSVM.h.

◆ fMaxVars

TVectorD* TMVA::MethodSVM::fMaxVars
private

Definition at line 141 of file MethodSVM.h.

◆ fmGamma

std::vector<Float_t> TMVA::MethodSVM::fmGamma
private

Definition at line 150 of file MethodSVM.h.

◆ fMinVars

TVectorD* TMVA::MethodSVM::fMinVars
private

Definition at line 140 of file MethodSVM.h.

◆ fMult

Float_t TMVA::MethodSVM::fMult
private

Definition at line 149 of file MethodSVM.h.

◆ fMultiKernels

std::string TMVA::MethodSVM::fMultiKernels
private

Definition at line 156 of file MethodSVM.h.

◆ fNSubSets

UShort_t TMVA::MethodSVM::fNSubSets
private

Definition at line 132 of file MethodSVM.h.

◆ fNumVars

Float_t TMVA::MethodSVM::fNumVars
private

Definition at line 151 of file MethodSVM.h.

◆ fOrder

Int_t TMVA::MethodSVM::fOrder
private

Definition at line 146 of file MethodSVM.h.

◆ fSupportVectors

std::vector<TMVA::SVEvent*>* TMVA::MethodSVM::fSupportVectors
private

Definition at line 137 of file MethodSVM.h.

◆ fSVKernelFunction

SVKernelFunction* TMVA::MethodSVM::fSVKernelFunction
private

Definition at line 138 of file MethodSVM.h.

◆ fTheKernel

TString TMVA::MethodSVM::fTheKernel
private

Definition at line 144 of file MethodSVM.h.

◆ fTheta

Float_t TMVA::MethodSVM::fTheta
private

Definition at line 147 of file MethodSVM.h.

◆ fTolerance

Float_t TMVA::MethodSVM::fTolerance
private

Definition at line 130 of file MethodSVM.h.

◆ fTune

std::string TMVA::MethodSVM::fTune
private

Definition at line 155 of file MethodSVM.h.

◆ fVarNames

std::vector<TString> TMVA::MethodSVM::fVarNames
private

Definition at line 152 of file MethodSVM.h.

◆ fWgSet

SVWorkingSet* TMVA::MethodSVM::fWgSet
private

Definition at line 135 of file MethodSVM.h.

Libraries for TMVA::MethodSVM:
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The documentation for this class was generated from the following files: