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ROOT 6.08/07 Reference Guide |
Definition at line 51 of file MethodTMlpANN.h.
Public Member Functions | |
MethodTMlpANN (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="3000:N-1:N-2") | |
standard constructor More... | |
MethodTMlpANN (DataSetInfo &theData, const TString &theWeightFile) | |
constructor from weight file More... | |
virtual | ~MethodTMlpANN (void) |
destructor More... | |
void | AddWeightsXMLTo (void *parent) const |
write weights to xml file More... | |
const Ranking * | CreateRanking () |
Double_t | GetMvaValue (Double_t *err=0, Double_t *errUpper=0) |
calculate the value of the neural net for the current event More... | |
virtual Bool_t | HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets) |
TMlpANN can handle classification with 2 classes. More... | |
void | MakeClass (const TString &classFileName=TString("")) const |
create reader class for classifier -> overwrites base class function create specific class for TMultiLayerPerceptron More... | |
void | ReadWeightsFromStream (std::istream &istr) |
read weights from stream since the MLP can not read from the stream, we 1st: write the weights to temporary file More... | |
void | ReadWeightsFromXML (void *wghtnode) |
rebuild temporary textfile from xml weightfile and load this file into MLP More... | |
void | SetHiddenLayer (TString hiddenlayer="") |
void | Train (void) |
performs TMlpANN training available learning methods: More... | |
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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 () |
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... | |
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IMethod () | |
virtual | ~IMethod () |
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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... | |
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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... | |
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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 | |
void | GetHelpMessage () const |
get help message text More... | |
void | MakeClassSpecific (std::ostream &, const TString &) const |
write specific classifier response nothing to do here - all taken care of by TMultiLayerPerceptron More... | |
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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 |
virtual void | MakeClassSpecificHeader (std::ostream &, const TString &="") 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 |
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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... | |
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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 | CreateMLPOptions (TString) |
translates options from option string into TMlpANN language More... | |
void | DeclareOptions () |
define the options (their key words) that can be set in the option string know options: NCycles <integer> Number of training cycles (too many cycles could overtrain the network) HiddenLayers <string> Layout of the hidden layers (nodes per layer) More... | |
void | Init (void) |
default initialisations More... | |
void | ProcessOptions () |
builds the neural network as specified by the user More... | |
Additional Inherited Members | |
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enum | EWeightFileType { kROOT =0, kTEXT } |
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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) } |
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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... | |
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Bool_t | fSetupCompleted |
const Event * | fTmpEvent |
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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 |
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MsgLogger * | fLogger |
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TString | fName |
TString | fTitle |
#include <TMVA/MethodTMlpANN.h>
TMVA::MethodTMlpANN::MethodTMlpANN | ( | const TString & | jobName, |
const TString & | methodTitle, | ||
DataSetInfo & | theData, | ||
const TString & | theOption = "3000:N-1:N-2" |
||
) |
standard constructor
Definition at line 97 of file MethodTMlpANN.cxx.
TMVA::MethodTMlpANN::MethodTMlpANN | ( | DataSetInfo & | theData, |
const TString & | theWeightFile | ||
) |
constructor from weight file
Definition at line 113 of file MethodTMlpANN.cxx.
|
virtual |
destructor
Definition at line 145 of file MethodTMlpANN.cxx.
write weights to xml file
Implements TMVA::MethodBase.
Definition at line 357 of file MethodTMlpANN.cxx.
translates options from option string into TMlpANN language
Definition at line 153 of file MethodTMlpANN.cxx.
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inlinevirtual |
Implements TMVA::MethodBase.
Definition at line 88 of file MethodTMlpANN.h.
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privatevirtual |
define the options (their key words) that can be set in the option string know options: NCycles <integer> Number of training cycles (too many cycles could overtrain the network) HiddenLayers <string> Layout of the hidden layers (nodes per layer)
Implements TMVA::MethodBase.
Definition at line 205 of file MethodTMlpANN.cxx.
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get help message text
typical length of text line: "|--------------------------------------------------------------|"
Implements TMVA::IMethod.
Definition at line 516 of file MethodTMlpANN.cxx.
calculate the value of the neural net for the current event
Implements TMVA::MethodBase.
Definition at line 240 of file MethodTMlpANN.cxx.
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TMlpANN can handle classification with 2 classes.
Implements TMVA::IMethod.
Definition at line 127 of file MethodTMlpANN.cxx.
default initialisations
Implements TMVA::MethodBase.
Definition at line 138 of file MethodTMlpANN.cxx.
create reader class for classifier -> overwrites base class function create specific class for TMultiLayerPerceptron
Reimplemented from TMVA::MethodBase.
Definition at line 488 of file MethodTMlpANN.cxx.
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write specific classifier response nothing to do here - all taken care of by TMultiLayerPerceptron
Reimplemented from TMVA::MethodBase.
Definition at line 506 of file MethodTMlpANN.cxx.
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builds the neural network as specified by the user
Implements TMVA::MethodBase.
Definition at line 225 of file MethodTMlpANN.cxx.
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read weights from stream since the MLP can not read from the stream, we 1st: write the weights to temporary file
Implements TMVA::MethodBase.
Definition at line 456 of file MethodTMlpANN.cxx.
rebuild temporary textfile from xml weightfile and load this file into MLP
Implements TMVA::MethodBase.
Definition at line 393 of file MethodTMlpANN.cxx.
Definition at line 85 of file MethodTMlpANN.h.
performs TMlpANN training available learning methods:
TMultiLayerPerceptron::kStochastic TMultiLayerPerceptron::kBatch TMultiLayerPerceptron::kSteepestDescent TMultiLayerPerceptron::kRibierePolak TMultiLayerPerceptron::kFletcherReeves TMultiLayerPerceptron::kBFGS
TMultiLayerPerceptron wants test and training tree at once so merge the training and testing trees from the MVA factory first:
Implements TMVA::MethodBase.
Definition at line 270 of file MethodTMlpANN.cxx.
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Definition at line 115 of file MethodTMlpANN.h.
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Definition at line 110 of file MethodTMlpANN.h.
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Definition at line 120 of file MethodTMlpANN.h.
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Definition at line 113 of file MethodTMlpANN.h.
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Definition at line 112 of file MethodTMlpANN.h.
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Definition at line 118 of file MethodTMlpANN.h.
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Definition at line 116 of file MethodTMlpANN.h.
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Definition at line 117 of file MethodTMlpANN.h.