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ROOT 6.07/09 Reference Guide |
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ROOT 6.07/09 Reference Guide |
Definition at line 100 of file MethodCFMlpANN.h.
Public Member Functions | |
| MethodCFMlpANN (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="3000:N-1:N-2") | |
| standard constructor option string: "n_training_cycles:n_hidden_layers" default is: n_training_cycles = 5000, n_layers = 4 More... | |
| MethodCFMlpANN (DataSetInfo &theData, const TString &theWeightFile) | |
| constructor from weight file More... | |
| virtual | ~MethodCFMlpANN (void) |
| destructor More... | |
| void | AddWeightsXMLTo (void *parent) const |
| write weights to xml file More... | |
| const Ranking * | CreateRanking () |
| Int_t | GetClass (Int_t ivar) const |
| Double_t | GetData (Int_t isel, Int_t ivar) const |
| Double_t | GetMvaValue (Double_t *err=0, Double_t *errUpper=0) |
| returns CFMlpANN output (normalised within [0,1]) More... | |
| virtual Bool_t | HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t) |
| CFMlpANN can handle classification with 2 classes. More... | |
| void | ReadWeightsFromStream (std::istream &istr) |
| read back the weight from the training from file (stream) More... | |
| void | ReadWeightsFromXML (void *wghtnode) |
| read weights from xml file More... | |
| void | Train (void) |
| training of the Clement-Ferrand NN classifier More... | |
 Public Member Functions inherited from TMVA::MethodBase | |
| MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="") | |
| standard constructur 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) |
| TDirectory * | BaseDir () 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... | |
| DataSet * | Data () const |
| DataSetInfo & | DataInfo () const |
| virtual void | DeclareCompatibilityOptions () |
| options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weightfile at hand More... | |
| 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 Event * | GetEvent () const |
| const Event * | GetEvent (const TMVA::Event *ev) const |
| const Event * | GetEvent (Long64_t ievt) const |
| const Event * | GetEvent (Long64_t ievt, Types::ETreeType type) const |
| const std::vector< TMVA::Event * > & | GetEventCollection (Types::ETreeType type) |
| returns the event collection (i.e. More... | |
| TFile * | GetFile () const |
| const TString & | GetInputLabel (Int_t i) const |
| const char * | GetInputTitle (Int_t i) const |
| const TString & | GetInputVar (Int_t i) const |
| TMultiGraph * | GetInteractiveTrainingError () |
| const TString & | GetJobName () 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, 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 TString & | GetMethodName () const |
| Types::EMVA | GetMethodType () const |
| TString | GetMethodTypeName () const |
| virtual std::vector< Float_t > | GetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity) |
| virtual std::vector< Float_t > | GetMulticlassTrainingEfficiency (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) = Integrate_[-oo..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) |
| virtual const std::vector< Float_t > & | GetRegressionValues () |
| 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> = (1/2) Int_-oo..+oo { (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> = (1/2) Int_-oo..+oo { (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 = |<S> - |/Sqrt(RMS_S2 + RMS_B2) More... | |
| const Event * | GetTestingEvent (Long64_t ievt) const |
| Double_t | GetTestTime () const |
| const TString & | GetTestvarName () const |
| virtual Double_t | GetTrainingEfficiency (const TString &) |
| const Event * | GetTrainingEvent (Long64_t ievt) const |
| 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 |
| TransformationHandler & | GetTransformationHandler (Bool_t takeReroutedIfAvailable=true) |
| const TransformationHandler & | GetTransformationHandler (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 () |
| 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 tbe selected as signal or background More... | |
| Bool_t | IsSilentFile () |
| virtual void | MakeClass (const TString &classFileName=TString("")) const |
| create reader class for method (classification only at present) More... | |
| TDirectory * | MethodBaseDir () const |
| returns the ROOT directory where all instances of the corresponding MVA method are stored More... | |
| virtual std::map< TString, Double_t > | OptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA") |
| call the Optimzier with the set of paremeters and ranges that are meant to be tuned. 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 | Reset () |
| 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) |
| virtual void | SetTuneParameters (std::map< TString, Double_t > tuneParameters) |
| set the tuning parameters accoding to the argument This is just a dummy . More... | |
| 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 destructur 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 > | |
| OptionBase * | DeclareOptionRef (T &ref, const TString &name, const TString &desc="") |
| template<class T > | |
| OptionBase * | DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="") |
| template<class T > | |
| TMVA::OptionBase * | DeclareOptionRef (T &ref, const TString &name, const TString &desc) |
| template<class T > | |
| TMVA::OptionBase * | DeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc) |
| const char * | GetConfigDescription () const |
| const char * | GetConfigName () const |
| const TString & | GetOptions () const |
| MsgLogger & | Log () 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 () |
| virtual void | Clear (Option_t *option="") |
| Set name and title to empty strings (""). More... | |
| virtual TObject * | Clone (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... | |
| TNamed & | operator= (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... | |
| 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 TObject * | DrawClone (Option_t *option="") const |
| Draw a clone of this object in the current pad. 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 TObject * | FindObject (const char *name) const |
| Must be redefined in derived classes. More... | |
| virtual TObject * | FindObject (const TObject *obj) const |
| Must be redefined in derived classes. More... | |
| virtual Option_t * | GetDrawOption () 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_t * | GetOption () 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... | |
| 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... | |
| Bool_t | IsOnHeap () const |
| 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... | |
| void * | operator new (size_t sz) |
| void * | operator new (size_t sz, void *vp) |
| void * | operator new[] (size_t sz) |
| void * | operator new[] (size_t sz, void *vp) |
| TObject & | operator= (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... | |
| 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 | |
| Int_t | DataInterface (Double_t *, Double_t *, Int_t *, Int_t *, Int_t *, Int_t *, Double_t *, Int_t *, Int_t *) |
| data interface function More... | |
| void | GetHelpMessage () const |
| get help message text More... | |
| void | MakeClassSpecific (std::ostream &, const TString &) const |
| void | MakeClassSpecificHeader (std::ostream &, const TString &="") const |
| write specific classifier response for header More... | |
| Protected Member Functions inherited from TMVA::MethodBase | |
| const TString & | GetInternalVarName (Int_t ivar) const |
| virtual std::vector< Double_t > | GetMvaValues (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 TString & | GetOriginalVarName (Int_t ivar) const |
| const TString & | GetWeightFileDir () const |
| Bool_t | HasTrainingTree () const |
| Bool_t | Help () const |
| Bool_t | IgnoreEventsWithNegWeightsInTraining () const |
| Bool_t | IsConstructedFromWeightFile () const |
| Bool_t | IsNormalised () const |
| void | NoErrorCalc (Double_t *const err, Double_t *const errUpper) |
| virtual void | ReadWeightsFromStream (TFile &) |
| 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 TString & | GetReferenceFile () const |
| Bool_t | LooseOptionCheckingEnabled () const |
| void | ResetSetFlag () |
| resets the IsSet falg 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 | DeclareOptions () |
| define the options (their key words) that can be set in the option string know options: NCycles=xx :the number of training cycles HiddenLayser="N-1,N-2" :the specification of the hidden layers More... | |
| Double_t | EvalANN (std::vector< Double_t > &, Bool_t &isOK) |
| evaluates NN value as function of input variables More... | |
| void | Init (void) |
| default initialisation called by all constructors More... | |
| void | NN_ava (Double_t *) |
| auxiliary functions More... | |
| Double_t | NN_fonc (Int_t, Double_t) const |
| activation function More... | |
| void | PrintWeights (std::ostream &o) const |
| write the weights of the neural net More... | |
| void | ProcessOptions () |
| decode the options in the option string More... | |
| Private Member Functions inherited from TMVA::MethodCFMlpANN_Utils | |
| MethodCFMlpANN_Utils () | |
| virtual | ~MethodCFMlpANN_Utils () |
| void | Arret (const char *mot) |
| void | CollectVar (Int_t *nvar, Int_t *class__, Double_t *xpg) |
| void | Cout (Int_t *, Double_t *xxx) |
| void | Cout2 (Int_t *, Double_t *yyy) |
| void | En_arriere (Int_t *ievent) |
| void | En_avant (Int_t *ievent) |
| void | En_avant2 (Int_t *ievent) |
| void | Entree_new (Int_t *, char *, Int_t *ntrain, Int_t *ntest, Int_t *numlayer, Int_t *nodes, Int_t *numcycle, Int_t) |
| Double_t | Fdecroi (Int_t *i__) |
| void | Foncf (Int_t *i__, Double_t *u, Double_t *f) |
| void | GraphNN (Int_t *ilearn, Double_t *, Double_t *, char *, Int_t) |
| void | Inl () |
| void | Innit (char *det, Double_t *tout2, Double_t *tin2, Int_t) |
| void | Lecev2 (Int_t *ktest, Double_t *tout2, Double_t *tin2) |
| void | Leclearn (Int_t *ktest, Double_t *tout2, Double_t *tin2) |
| void | Out (Int_t *iii, Int_t *maxcycle) |
| Double_t | Sen3a (void) |
| void | SetLogger (MsgLogger *l) |
| void | TestNN () |
| void | Train_nn (Double_t *tin2, Double_t *tout2, Int_t *ntrain, Int_t *ntest, Int_t *nvar2, Int_t *nlayer, Int_t *nodes, Int_t *ncycle) |
| Double_t | W_ref (const Double_t wNN[], Int_t a_1, Int_t a_2, Int_t a_3) const |
| Double_t & | W_ref (Double_t wNN[], Int_t a_1, Int_t a_2, Int_t a_3) |
| void | Wini () |
| Double_t | Ww_ref (const Double_t wwNN[], Int_t a_1, Int_t a_2) const |
| Double_t & | Ww_ref (Double_t wwNN[], Int_t a_1, Int_t a_2) |
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, kBitMask = 0x00ffffff } |
| enum | { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) } |
| enum | EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = 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 Event * | fTmpEvent |
| Protected Attributes inherited from TMVA::MethodBase | |
| Types::EAnalysisType | fAnalysisType |
| UInt_t | fBackgroundClass |
| bool | fExitFromTraining = false |
| std::vector< TString > * | fInputVars |
| IPythonInteractive * | fInteractive = nullptr |
| UInt_t | fIPyCurrentIter = 0 |
| UInt_t | fIPyMaxIter = 0 |
| std::vector< Float_t > * | fMulticlassReturnVal |
| Int_t | fNbins |
| Int_t | fNbinsH |
| Int_t | fNbinsMVAoutput |
| Ranking * | fRanking |
| std::vector< Float_t > * | fRegressionReturnVal |
| Results * | fResults |
| UInt_t | fSignalClass |
| Protected Attributes inherited from TMVA::Configurable | |
| MsgLogger * | fLogger |
| Protected Attributes inherited from TNamed | |
| TString | fName |
| TString | fTitle |
| Static Private Attributes inherited from TMVA::MethodCFMlpANN_Utils | |
| static const Int_t | fg_max_nNodes_ = max_nNodes_ |
| static const Int_t | fg_max_nVar_ = max_nVar_ |
| static const char *const | fg_MethodName = "--- CFMlpANN " |
#include <TMVA/MethodCFMlpANN.h>
| TMVA::MethodCFMlpANN::MethodCFMlpANN | ( | const TString & | jobName, |
| const TString & | methodTitle, | ||
| DataSetInfo & | theData, | ||
| const TString & | theOption = "3000:N-1:N-2" |
||
| ) |
standard constructor option string: "n_training_cycles:n_hidden_layers" default is: n_training_cycles = 5000, n_layers = 4
since there is one input and one output layer. The number of nodes (neurons) is predefined to be: n_nodes[i] = nvars + 1 - i (where i=1..n_layers)
with nvars being the number of variables used in the NN.
Hence, the default case is: n_neurons(layer 1 (input)) : nvars n_neurons(layer 2 (hidden)): nvars-1 n_neurons(layer 3 (hidden)): nvars-1 n_neurons(layer 4 (out)) : 2
This artificial neural network usually needs a relatively large number of cycles to converge (8000 and more). Overtraining can be efficienctly tested by comparing the signal and background output of the NN for the events that were used for training and an independent data sample (with equal properties). If the separation performance is significantly better for the training sample, the NN interprets statistical effects, and is hence overtrained. In this case, the number of cycles should be reduced, or the size of the training sample increased.
Definition at line 129 of file MethodCFMlpANN.cxx.
| TMVA::MethodCFMlpANN::MethodCFMlpANN | ( | DataSetInfo & | theData, |
| const TString & | theWeightFile | ||
| ) |
constructor from weight file
Definition at line 148 of file MethodCFMlpANN.cxx.
|
virtual |
destructor
Definition at line 268 of file MethodCFMlpANN.cxx.
write weights to xml file
Implements TMVA::MethodBase.
Definition at line 536 of file MethodCFMlpANN.cxx.
|
inlinevirtual |
Implements TMVA::MethodBase.
Definition at line 136 of file MethodCFMlpANN.h.
|
protectedvirtual |
data interface function
Implements TMVA::MethodCFMlpANN_Utils.
Definition at line 505 of file MethodCFMlpANN.cxx.
|
privatevirtual |
define the options (their key words) that can be set in the option string know options: NCycles=xx :the number of training cycles HiddenLayser="N-1,N-2" :the specification of the hidden layers
Implements TMVA::MethodBase.
Definition at line 175 of file MethodCFMlpANN.cxx.
evaluates NN value as function of input variables
Definition at line 342 of file MethodCFMlpANN.cxx.
Definition at line 132 of file MethodCFMlpANN.h.
Definition at line 131 of file MethodCFMlpANN.h.
|
protectedvirtual |
get help message text
typical length of text line: "|--------------------------------------------------------------|"
Implements TMVA::IMethod.
Definition at line 708 of file MethodCFMlpANN.cxx.
returns CFMlpANN output (normalised within [0,1])
Implements TMVA::MethodBase.
Definition at line 320 of file MethodCFMlpANN.cxx.
|
virtual |
CFMlpANN can handle classification with 2 classes.
Implements TMVA::IMethod.
Definition at line 164 of file MethodCFMlpANN.cxx.
default initialisation called by all constructors
Implements TMVA::MethodBase.
Definition at line 256 of file MethodCFMlpANN.cxx.
|
protectedvirtual |
Reimplemented from TMVA::MethodBase.
Definition at line 688 of file MethodCFMlpANN.cxx.
|
protectedvirtual |
write specific classifier response for header
Reimplemented from TMVA::MethodBase.
Definition at line 698 of file MethodCFMlpANN.cxx.
auxiliary functions
Definition at line 376 of file MethodCFMlpANN.cxx.
activation function
Definition at line 396 of file MethodCFMlpANN.cxx.
|
private |
write the weights of the neural net
Definition at line 629 of file MethodCFMlpANN.cxx.
|
privatevirtual |
decode the options in the option string
Implements TMVA::MethodBase.
Definition at line 184 of file MethodCFMlpANN.cxx.
|
virtual |
read back the weight from the training from file (stream)
Implements TMVA::MethodBase.
Definition at line 413 of file MethodCFMlpANN.cxx.
read weights from xml file
Implements TMVA::MethodBase.
Definition at line 580 of file MethodCFMlpANN.cxx.
training of the Clement-Ferrand NN classifier
Implements TMVA::MethodBase.
Definition at line 284 of file MethodCFMlpANN.cxx.
|
private |
Definition at line 162 of file MethodCFMlpANN.h.
|
private |
Definition at line 161 of file MethodCFMlpANN.h.
|
private |
Definition at line 170 of file MethodCFMlpANN.h.
|
private |
Definition at line 165 of file MethodCFMlpANN.h.
|
private |
Definition at line 164 of file MethodCFMlpANN.h.
|
private |
Definition at line 166 of file MethodCFMlpANN.h.
|
private |
Definition at line 169 of file MethodCFMlpANN.h.
|
private |
Definition at line 171 of file MethodCFMlpANN.h.
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