ROOT 6.08/07 Reference Guide |
Definition at line 80 of file MethodANNBase.h.
Public Types | |
enum | EEstimator { kMSE =0, kCE } |
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) } |
Public Member Functions | |
MethodANNBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &theData, const TString &theOption) | |
standard constructor Note: Right now it is an option to choose the neuron input function, but only the input function "sum" leads to weight convergence – otherwise the weights go to nan and lead to an ABORT. More... | |
MethodANNBase (Types::EMVA methodType, DataSetInfo &theData, const TString &theWeightFile) | |
construct the Method from the weight file More... | |
virtual | ~MethodANNBase () |
destructor More... | |
void | AddWeightsXMLTo (void *parent) const |
create XML description of ANN classifier More... | |
const Ranking * | CreateRanking () |
compute ranking of input variables by summing function of weights More... | |
Bool_t | Debug () const |
who the hell makes such strange Debug flags that even use "global pointers".. More... | |
virtual void | DeclareOptions () |
define the options (their key words) that can be set in the option string here the options valid for ALL MVA methods are declared. More... | |
template<typename WriteIterator > | |
void | GetLayerActivation (size_t layer, WriteIterator writeIterator) |
virtual const std::vector< Float_t > & | GetMulticlassValues () |
get the multiclass classification values generated by the NN More... | |
virtual Double_t | GetMvaValue (Double_t *err=0, Double_t *errUpper=0) |
get the mva value generated by the NN More... | |
virtual const std::vector< Float_t > & | GetRegressionValues () |
get the regression value generated by the NN More... | |
void | InitANNBase () |
initialize ANNBase object More... | |
virtual void | PrintNetwork () const |
print network representation, for debugging More... | |
virtual void | ProcessOptions () |
do nothing specific at this moment More... | |
virtual void | ReadWeightsFromStream (std::istream &istr) |
destroy/clear the network then read it back in from the weights file More... | |
void | ReadWeightsFromXML (void *wghtnode) |
read MLP from xml weight file More... | |
void | SetActivation (TActivation *activation) |
void | SetNeuronInputCalculator (TNeuronInput *inputCalculator) |
virtual void | Train ()=0 |
virtual void | WriteMonitoringHistosToFile () const |
write histograms 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 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) |
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) |
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 |
virtual void | Init ()=0 |
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... | |
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 () |
virtual Bool_t | HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)=0 |
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... | |
Public Attributes | |
TObjArray * | fNetwork |
Public Attributes inherited from TMVA::MethodBase | |
Bool_t | fSetupCompleted |
const Event * | fTmpEvent |
Protected Member Functions | |
virtual void | BuildNetwork (std::vector< Int_t > *layout, std::vector< Double_t > *weights=NULL, Bool_t fromFile=kFALSE) |
build network given a layout (number of neurons in each layer) and optional weights array More... | |
void | CreateWeightMonitoringHists (const TString &bulkname, std::vector< TH1 *> *hv=0) const |
void | ForceNetworkCalculations () |
calculate input values to each neuron More... | |
void | ForceNetworkInputs (const Event *ev, Int_t ignoreIndex=-1) |
force the input values of the input neurons force the value for each input neuron More... | |
TNeuron * | GetInputNeuron (Int_t index) |
Double_t | GetNetworkOutput () |
TNeuron * | GetOutputNeuron (Int_t index=0) |
virtual void | MakeClassSpecific (std::ostream &, const TString &) const |
write specific classifier response More... | |
Int_t | NumCycles () |
std::vector< Int_t > * | ParseLayoutString (TString layerSpec) |
parse layout specification string and return a vector, each entry containing the number of neurons to go in each successive layer More... | |
void | PrintMessage (TString message, Bool_t force=kFALSE) const |
print messages, turn off printing by setting verbose and debug flag appropriately More... | |
void | WaitForKeyboard () |
wait for keyboard input, for debugging 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 |
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 |
Protected Member Functions inherited from TMVA::IMethod | |
virtual void | GetHelpMessage () const =0 |
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 | AddPreLinks (TNeuron *neuron, TObjArray *prevLayer) |
add synapses connecting a neuron to its preceding layer More... | |
void | BuildLayer (Int_t numNeurons, TObjArray *curLayer, TObjArray *prevLayer, Int_t layerIndex, Int_t numLayers, Bool_t from_file=false) |
build a single layer with neurons and synapses connecting this layer to the previous layer More... | |
void | BuildLayers (std::vector< Int_t > *layout, Bool_t from_file=false) |
build the network layers More... | |
void | DeleteNetwork () |
delete/clear network More... | |
void | DeleteNetworkLayer (TObjArray *&layer) |
delete a network layer More... | |
void | ForceWeights (std::vector< Double_t > *weights) |
force the synapse weights More... | |
void | InitWeights () |
initialize the synapse weights randomly More... | |
void | PrintLayer (TObjArray *layer) const |
print a single layer, for debugging More... | |
void | PrintNeuron (TNeuron *neuron) const |
print a neuron, for debugging More... | |
Private Attributes | |
TObjArray * | fInputLayer |
TString | fLayerSpec |
std::vector< TNeuron * > | fOutputNeurons |
Static Private Attributes | |
static const Bool_t | fgDEBUG = kTRUE |
Additional Inherited Members | |
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... | |
#include <TMVA/MethodANNBase.h>
Enumerator | |
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kMSE | |
kCE |
Definition at line 155 of file MethodANNBase.h.
TMVA::MethodANNBase::MethodANNBase | ( | const TString & | jobName, |
Types::EMVA | methodType, | ||
const TString & | methodTitle, | ||
DataSetInfo & | theData, | ||
const TString & | theOption | ||
) |
standard constructor Note: Right now it is an option to choose the neuron input function, but only the input function "sum" leads to weight convergence – otherwise the weights go to nan and lead to an ABORT.
Definition at line 84 of file MethodANNBase.cxx.
TMVA::MethodANNBase::MethodANNBase | ( | Types::EMVA | methodType, |
DataSetInfo & | theData, | ||
const TString & | theWeightFile | ||
) |
construct the Method from the weight file
Definition at line 102 of file MethodANNBase.cxx.
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virtual |
destructor
Definition at line 238 of file MethodANNBase.cxx.
add synapses connecting a neuron to its preceding layer
Definition at line 426 of file MethodANNBase.cxx.
create XML description of ANN classifier
Implements TMVA::MethodBase.
Definition at line 715 of file MethodANNBase.cxx.
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build a single layer with neurons and synapses connecting this layer to the previous layer
Definition at line 374 of file MethodANNBase.cxx.
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build the network layers
Definition at line 338 of file MethodANNBase.cxx.
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build network given a layout (number of neurons in each layer) and optional weights array
Definition at line 293 of file MethodANNBase.cxx.
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compute ranking of input variables by summing function of weights
Implements TMVA::MethodBase.
Definition at line 927 of file MethodANNBase.cxx.
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Definition at line 969 of file MethodANNBase.cxx.
Bool_t TMVA::MethodANNBase::Debug | ( | ) | const |
who the hell makes such strange Debug flags that even use "global pointers"..
Definition at line 1170 of file MethodANNBase.cxx.
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define the options (their key words) that can be set in the option string here the options valid for ALL MVA methods are declared.
know options: NCycles=xx :the number of training cycles Normalize=kTRUE,kFALSe :if normalised in put variables should be used HiddenLayser="N-1,N-2" :the specification of the hidden layers NeuronType=sigmoid,tanh,radial,linar : the type of activation function used at the neuronn
Implements TMVA::MethodBase.
Reimplemented in TMVA::MethodMLP.
Definition at line 125 of file MethodANNBase.cxx.
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delete/clear network
Definition at line 246 of file MethodANNBase.cxx.
delete a network layer
Definition at line 277 of file MethodANNBase.cxx.
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calculate input values to each neuron
Definition at line 495 of file MethodANNBase.cxx.
force the input values of the input neurons force the value for each input neuron
Definition at line 477 of file MethodANNBase.cxx.
force the synapse weights
Definition at line 461 of file MethodANNBase.cxx.
Definition at line 176 of file MethodANNBase.h.
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inline |
Definition at line 250 of file MethodANNBase.h.
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get the multiclass classification values generated by the NN
Reimplemented from TMVA::MethodBase.
Definition at line 672 of file MethodANNBase.cxx.
get the mva value generated by the NN
Implements TMVA::MethodBase.
Reimplemented in TMVA::MethodMLP.
Definition at line 598 of file MethodANNBase.cxx.
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inlineprotected |
Definition at line 167 of file MethodANNBase.h.
Definition at line 177 of file MethodANNBase.h.
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get the regression value generated by the NN
Reimplemented from TMVA::MethodBase.
Definition at line 625 of file MethodANNBase.cxx.
void TMVA::MethodANNBase::InitANNBase | ( | ) |
initialize ANNBase object
Definition at line 209 of file MethodANNBase.cxx.
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private |
initialize the synapse weights randomly
Definition at line 445 of file MethodANNBase.cxx.
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protectedvirtual |
write specific classifier response
Reimplemented from TMVA::MethodBase.
Reimplemented in TMVA::MethodMLP.
Definition at line 1052 of file MethodANNBase.cxx.
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inlineprotected |
Definition at line 175 of file MethodANNBase.h.
parse layout specification string and return a vector, each entry containing the number of neurons to go in each successive layer
Definition at line 172 of file MethodANNBase.cxx.
print a single layer, for debugging
Definition at line 565 of file MethodANNBase.cxx.
print messages, turn off printing by setting verbose and debug flag appropriately
Definition at line 518 of file MethodANNBase.cxx.
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virtual |
print network representation, for debugging
Definition at line 541 of file MethodANNBase.cxx.
print a neuron, for debugging
Definition at line 581 of file MethodANNBase.cxx.
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do nothing specific at this moment
Implements TMVA::MethodBase.
Reimplemented in TMVA::MethodMLP.
Definition at line 157 of file MethodANNBase.cxx.
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destroy/clear the network then read it back in from the weights file
Implements TMVA::MethodBase.
Definition at line 906 of file MethodANNBase.cxx.
read MLP from xml weight file
Implements TMVA::MethodBase.
Definition at line 783 of file MethodANNBase.cxx.
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inline |
Definition at line 101 of file MethodANNBase.h.
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inline |
Definition at line 105 of file MethodANNBase.h.
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pure virtual |
Implements TMVA::MethodBase.
Implemented in TMVA::MethodMLP.
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protected |
wait for keyboard input, for debugging
Definition at line 526 of file MethodANNBase.cxx.
write histograms to file
Reimplemented from TMVA::MethodBase.
Definition at line 1010 of file MethodANNBase.cxx.
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Definition at line 181 of file MethodANNBase.h.
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protected |
Definition at line 199 of file MethodANNBase.h.
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Definition at line 198 of file MethodANNBase.h.
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Definition at line 200 of file MethodANNBase.h.
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Definition at line 189 of file MethodANNBase.h.
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Definition at line 194 of file MethodANNBase.h.
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Definition at line 193 of file MethodANNBase.h.
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Definition at line 190 of file MethodANNBase.h.
Definition at line 242 of file MethodANNBase.h.
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Definition at line 183 of file MethodANNBase.h.
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Definition at line 185 of file MethodANNBase.h.
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Definition at line 237 of file MethodANNBase.h.
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Definition at line 204 of file MethodANNBase.h.
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Definition at line 239 of file MethodANNBase.h.
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Definition at line 210 of file MethodANNBase.h.
TObjArray* TMVA::MethodANNBase::fNetwork |
Definition at line 157 of file MethodANNBase.h.
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Definition at line 213 of file MethodANNBase.h.
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Definition at line 212 of file MethodANNBase.h.
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Definition at line 182 of file MethodANNBase.h.
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Definition at line 238 of file MethodANNBase.h.
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Definition at line 208 of file MethodANNBase.h.
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Definition at line 187 of file MethodANNBase.h.
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Definition at line 188 of file MethodANNBase.h.
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Definition at line 184 of file MethodANNBase.h.
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Definition at line 180 of file MethodANNBase.h.
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Definition at line 205 of file MethodANNBase.h.