ROOT 6.14/05 Reference Guide |
This is a generalization of the above Likelihood methods to N_{var} dimensions, where N_{var} is the number of input variables used in the MVA.
If the multi-dimensional probability density functions (PDFs) for signal and background were known, this method contains the entire physical information, and is therefore optimal. Usually, kernel estimation methods are used to approximate the PDFs using the events from the training sample.
A very simple probability density estimator (PDE) has been suggested in hep-ex/0211019. The PDE for a given test event is obtained from counting the (normalized) number of signal and background (training) events that occur in the "vicinity" of the test event. The volume that describes "vicinity" is user-defined. A search method based on binary-trees is used to effectively reduce the selection time for the range search. Three different volume definitions are optional:
The adaptive range search is used by default.
Definition at line 59 of file MethodPDERS.h.
Public Member Functions | |
MethodPDERS (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption) | |
standard constructor for the PDERS method More... | |
MethodPDERS (DataSetInfo &theData, const TString &theWeightFile) | |
construct MethodPDERS through from file More... | |
virtual | ~MethodPDERS (void) |
destructor More... | |
void | AddWeightsXMLTo (void *parent) const |
write weights to xml file More... | |
Double_t | GetMvaValue (Double_t *err=0, Double_t *errUpper=0) |
init the size of a volume element using a defined fraction of the volume containing the entire events More... | |
const std::vector< Float_t > & | GetRegressionValues () |
Double_t | GetVolumeContentForRoot (Double_t) |
count number of events in rescaled volume More... | |
virtual Bool_t | HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets) |
PDERS can handle classification with 2 classes and regression with one or more regression-targets. More... | |
void | ReadWeightsFromStream (std::istream &istr) |
read weight info from file More... | |
void | ReadWeightsFromStream (TFile &istr) |
read training sample from file More... | |
void | ReadWeightsFromXML (void *wghtnode) |
void | Train (void) |
this is a dummy training: the preparation work to do is the construction of the binary tree as a pointer chain. More... | |
void | WriteWeightsToStream (TFile &rf) const |
write training sample (TTree) to file More... | |
Public Member Functions inherited from TMVA::MethodBase | |
MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="") | |
standard constructor More... | |
MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile) | |
constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More... | |
virtual | ~MethodBase () |
destructor More... | |
void | AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType) |
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 weight file 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, \frac{S}{\sqrt{S^2 + B^2}} , curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More... | |
UInt_t | GetMaxIter () |
Double_t | GetMean (Int_t ivar) const |
const TString & | GetMethodName () const |
Types::EMVA | GetMethodType () const |
TString | GetMethodTypeName () const |
virtual TMatrixD | GetMulticlassConfusionMatrix (Double_t effB, Types::ETreeType type) |
Construct a confusion matrix for a multiclass classifier. More... | |
virtual std::vector< Float_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) = \int_{[-\infty..x]} { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution More... | |
virtual void | GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const |
const std::vector< Float_t > & | GetRegressionValues (const TMVA::Event *const ev) |
Double_t | GetRMS (Int_t ivar) const |
virtual Double_t | GetROCIntegral (TH1D *histS, TH1D *histB) const |
calculate the area (integral) under the ROC curve as a overall quality measure of the classification More... | |
virtual Double_t | GetROCIntegral (PDF *pdfS=0, PDF *pdfB=0) const |
calculate the area (integral) under the ROC curve as a overall quality measure of the classification More... | |
virtual Double_t | GetSeparation (TH1 *, TH1 *) const |
compute "separation" defined as <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } More... | |
virtual Double_t | GetSeparation (PDF *pdfS=0, PDF *pdfB=0) const |
compute "separation" defined as <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } More... | |
Double_t | GetSignalReferenceCut () const |
Double_t | GetSignalReferenceCutOrientation () const |
virtual Double_t | GetSignificance () const |
compute significance of mean difference significance = \frac{|<S> - <B>|}{\sqrt{RMS_{S2} + RMS_{B2}}} More... | |
const 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 be 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 Optimizer with the set of parameters 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 according 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 destructor More... | |
void | AddOptionsXMLTo (void *parent) const |
write options to XML file More... | |
template<class T > | |
void | AddPreDefVal (const T &) |
template<class T > | |
void | AddPreDefVal (const TString &optname, const T &) |
void | CheckForUnusedOptions () const |
checks for unused options in option string More... | |
template<class T > | |
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 () |
TNamed destructor. More... | |
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... | |
ULong_t | CheckedHash () |
Checked and record whether for this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More... | |
virtual const char * | ClassName () const |
Returns name of class to which the object belongs. More... | |
virtual void | Delete (Option_t *option="") |
Delete this object. More... | |
virtual Int_t | DistancetoPrimitive (Int_t px, Int_t py) |
Computes distance from point (px,py) to the object. More... | |
virtual void | Draw (Option_t *option="") |
Default Draw method for all objects. More... | |
virtual void | DrawClass () const |
Draw class inheritance tree of the class to which this object belongs. More... | |
virtual TObject * | DrawClone (Option_t *option="") const |
Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad) . More... | |
virtual void | Dump () const |
Dump contents of object on stdout. More... | |
virtual void | Error (const char *method, const char *msgfmt,...) const |
Issue error message. More... | |
virtual void | Execute (const char *method, const char *params, Int_t *error=0) |
Execute method on this object with the given parameter string, e.g. More... | |
virtual void | Execute (TMethod *method, TObjArray *params, Int_t *error=0) |
Execute method on this object with parameters stored in the TObjArray. More... | |
virtual void | ExecuteEvent (Int_t event, Int_t px, Int_t py) |
Execute action corresponding to an event at (px,py). More... | |
virtual void | Fatal (const char *method, const char *msgfmt,...) const |
Issue fatal error message. More... | |
virtual 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... | |
Bool_t | HasInconsistentHash () const |
Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. More... | |
virtual void | Info (const char *method, const char *msgfmt,...) const |
Issue info message. More... | |
virtual Bool_t | InheritsFrom (const char *classname) const |
Returns kTRUE if object inherits from class "classname". More... | |
virtual Bool_t | InheritsFrom (const TClass *cl) const |
Returns kTRUE if object inherits from TClass cl. More... | |
virtual void | Inspect () const |
Dump contents of this object in a graphics canvas. More... | |
void | InvertBit (UInt_t f) |
virtual Bool_t | IsEqual (const TObject *obj) const |
Default equal comparison (objects are equal if they have the same address in memory). More... | |
virtual Bool_t | IsFolder () const |
Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More... | |
R__ALWAYS_INLINE Bool_t | IsOnHeap () const |
R__ALWAYS_INLINE Bool_t | IsZombie () const |
void | MayNotUse (const char *method) const |
Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More... | |
virtual Bool_t | Notify () |
This method must be overridden to handle object notification. More... | |
void | Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const |
Use this method to declare a method obsolete. More... | |
void | operator delete (void *ptr) |
Operator delete. More... | |
void | operator delete[] (void *ptr) |
Operator delete []. More... | |
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... | |
R__ALWAYS_INLINE Bool_t | TestBit (UInt_t f) const |
Int_t | TestBits (UInt_t f) const |
virtual void | UseCurrentStyle () |
Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More... | |
virtual void | Warning (const char *method, const char *msgfmt,...) const |
Issue warning message. More... | |
virtual Int_t | Write (const char *name=0, Int_t option=0, Int_t bufsize=0) |
Write this object to the current directory. More... | |
virtual Int_t | Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const |
Write this object to the current directory. More... | |
Static Public Member Functions | |
static Double_t | IGetVolumeContentForRoot (Double_t) |
Interface to RootFinder. More... | |
static MethodPDERS * | ThisPDERS (void) |
static pointer to this object More... | |
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... | |
Protected Member Functions | |
Double_t | ApplyKernelFunction (Double_t normalized_distance) |
from the normalized euclidean distance calculate the distance for a certain kernel More... | |
Double_t | CKernelEstimate (const Event &, std::vector< const BinarySearchTreeNode *> &, Volume &) |
normalization factors so we can work with radius 1 hyperspheres More... | |
const Ranking * | CreateRanking () |
BinarySearchTree * | GetBinaryTree (void) const |
void | GetHelpMessage () const |
get help message text More... | |
Double_t | GetNormalizedDistance (const TMVA::Event &base_event, const BinarySearchTreeNode &sample_event, Double_t *dim_normalization) |
We use Euclidian metric here. Might not be best or most efficient. More... | |
Double_t | KernelNormalization (Double_t pdf) |
Calculating the normalization factor only once (might need a reset at some point. More... | |
Double_t | LanczosFilter (Int_t level, Double_t x) |
Lanczos Filter. More... | |
void | MakeClassSpecific (std::ostream &, const TString &) const |
write specific classifier response More... | |
Double_t | NormSinc (Double_t x) |
NormSinc. More... | |
void | RKernelEstimate (const Event &, std::vector< const BinarySearchTreeNode *> &, Volume &, std::vector< Float_t > *pdfSum) |
normalization factors so we can work with radius 1 hyperspheres 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) |
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 flag for all declare options to be called before options are read from stream More... | |
void | WriteOptionsReferenceToFile () |
write complete options to output stream More... | |
Protected Member Functions inherited from TObject | |
virtual void | DoError (int level, const char *location, const char *fmt, va_list va) const |
Interface to ErrorHandler (protected). More... | |
void | MakeZombie () |
Protected Attributes | |
Int_t | fFcnCall |
Volume * | fHelpVolume |
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 |
Private Types | |
enum | EKernelEstimator { kBox = 0, kSphere, kTeepee, kGauss, kSinc3, kSinc5, kSinc7, kSinc9, kSinc11, kLanczos2, kLanczos3, kLanczos5, kLanczos8, kTrim } |
enum | EVolumeRangeMode { kUnsupported = 0, kMinMax, kRMS, kAdaptive, kUnscaled, kkNN } |
Private Member Functions | |
void | CalcAverages () |
compute also average RMS values required for adaptive Gaussian More... | |
void | CreateBinarySearchTree (Types::ETreeType type) |
create binary search trees for signal and background More... | |
Double_t | CRScalc (const Event &) |
void | DeclareOptions () |
define the options (their key words) that can be set in the option string. More... | |
Float_t | GetError (Float_t countS, Float_t countB, Float_t sumW2S, Float_t sumW2B) const |
statistical error estimate for RS estimator More... | |
void | GetSample (const Event &e, std::vector< const BinarySearchTreeNode *> &events, Volume *volume) |
void | Init (void) |
default initialisation routine called by all constructors More... | |
void | ProcessOptions () |
process the options specified by the user More... | |
void | RRScalc (const Event &, std::vector< Float_t > *count) |
void | SetVolumeElement (void) |
defines volume dimensions More... | |
void | UpdateThis () |
update static this pointer More... | |
Static Private Member Functions | |
static MethodPDERS *& | GetMethodPDERSThreadLocal () |
Private Attributes | |
std::vector< Float_t > | fAverageRMS |
BinarySearchTree * | fBinaryTree |
std::vector< Float_t > * | fDelta |
Float_t | fDeltaFrac |
Double_t | fGaussSigma |
Double_t | fGaussSigmaNorm |
Bool_t | fInitializedVolumeEle |
Float_t | fInitialScale |
enum TMVA::MethodPDERS::EKernelEstimator | fKernelEstimator |
TString | fKernelString |
Int_t | fkNNMax |
Int_t | fkNNMin |
Double_t | fMax_distance |
Float_t | fMaxVIterations |
Float_t | fNEventsMax |
Float_t | fNEventsMin |
Bool_t | fNormTree |
Double_t | fNRegOut |
Bool_t | fPrinted |
Float_t | fScaleB |
Float_t | fScaleS |
std::vector< Float_t > * | fShift |
TString | fVolumeRange |
enum TMVA::MethodPDERS::EVolumeRangeMode | fVRangeMode |
Additional Inherited Members | |
Public Types inherited from TMVA::MethodBase | |
enum | EWeightFileType { kROOT =0, kTEXT } |
Public Types inherited from TObject | |
enum | { kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000, kBitMask = 0x00ffffff } |
enum | { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) } |
enum | EDeprecatedStatusBits { kObjInCanvas = BIT(3) } |
enum | EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) } |
Public Attributes inherited from TMVA::MethodBase | |
Bool_t | fSetupCompleted |
const Event * | fTmpEvent |
#include <TMVA/MethodPDERS.h>
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Enumerator | |
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kBox | |
kSphere | |
kTeepee | |
kGauss | |
kSinc3 | |
kSinc5 | |
kSinc7 | |
kSinc9 | |
kSinc11 | |
kLanczos2 | |
kLanczos3 | |
kLanczos5 | |
kLanczos8 | |
kTrim |
Definition at line 158 of file MethodPDERS.h.
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Enumerator | |
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kUnsupported | |
kMinMax | |
kRMS | |
kAdaptive | |
kUnscaled | |
kkNN |
Definition at line 149 of file MethodPDERS.h.
TMVA::MethodPDERS::MethodPDERS | ( | const TString & | jobName, |
const TString & | methodTitle, | ||
DataSetInfo & | theData, | ||
const TString & | theOption | ||
) |
standard constructor for the PDERS method
Definition at line 102 of file MethodPDERS.cxx.
TMVA::MethodPDERS::MethodPDERS | ( | DataSetInfo & | theData, |
const TString & | theWeightFile | ||
) |
construct MethodPDERS through from file
Definition at line 136 of file MethodPDERS.cxx.
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virtual |
destructor
Definition at line 210 of file MethodPDERS.cxx.
write weights to xml file
Implements TMVA::MethodBase.
Definition at line 1101 of file MethodPDERS.cxx.
from the normalized euclidean distance calculate the distance for a certain kernel
Definition at line 924 of file MethodPDERS.cxx.
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compute also average RMS values required for adaptive Gaussian
Definition at line 435 of file MethodPDERS.cxx.
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normalization factors so we can work with radius 1 hyperspheres
Definition at line 836 of file MethodPDERS.cxx.
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create binary search trees for signal and background
Definition at line 457 of file MethodPDERS.cxx.
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inlineprotectedvirtual |
Implements TMVA::MethodBase.
Definition at line 128 of file MethodPDERS.h.
Definition at line 780 of file MethodPDERS.cxx.
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define the options (their key words) that can be set in the option string.
know options:
Implements TMVA::MethodBase.
Definition at line 254 of file MethodPDERS.cxx.
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inlineprotected |
Definition at line 114 of file MethodPDERS.h.
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statistical error estimate for RS estimator
Definition at line 1082 of file MethodPDERS.cxx.
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protectedvirtual |
get help message text
typical length of text line: "|--------------------------------------------------------------|"
Implements TMVA::IMethod.
Definition at line 1211 of file MethodPDERS.cxx.
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inlinestaticprivate |
Definition at line 214 of file MethodPDERS.h.
init the size of a volume element using a defined fraction of the volume containing the entire events
Implements TMVA::MethodBase.
Definition at line 372 of file MethodPDERS.cxx.
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We use Euclidian metric here. Might not be best or most efficient.
Definition at line 1024 of file MethodPDERS.cxx.
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Reimplemented from TMVA::MethodBase.
Definition at line 392 of file MethodPDERS.cxx.
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Definition at line 550 of file MethodPDERS.cxx.
count number of events in rescaled volume
Definition at line 539 of file MethodPDERS.cxx.
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PDERS can handle classification with 2 classes and regression with one or more regression-targets.
Implements TMVA::IMethod.
Definition at line 168 of file MethodPDERS.cxx.
Interface to RootFinder.
Definition at line 531 of file MethodPDERS.cxx.
default initialisation routine called by all constructors
Implements TMVA::MethodBase.
Definition at line 178 of file MethodPDERS.cxx.
Calculating the normalization factor only once (might need a reset at some point.
Can the method be restarted with different params?)
Definition at line 976 of file MethodPDERS.cxx.
Lanczos Filter.
Definition at line 1062 of file MethodPDERS.cxx.
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write specific classifier response
Reimplemented from TMVA::MethodBase.
Definition at line 1199 of file MethodPDERS.cxx.
NormSinc.
Definition at line 1041 of file MethodPDERS.cxx.
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privatevirtual |
process the options specified by the user
Implements TMVA::MethodBase.
Definition at line 291 of file MethodPDERS.cxx.
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virtual |
read weight info from file
Implements TMVA::MethodBase.
Definition at line 1140 of file MethodPDERS.cxx.
read training sample from file
Reimplemented from TMVA::MethodBase.
Definition at line 1177 of file MethodPDERS.cxx.
Implements TMVA::MethodBase.
Definition at line 1113 of file MethodPDERS.cxx.
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protected |
normalization factors so we can work with radius 1 hyperspheres
Definition at line 877 of file MethodPDERS.cxx.
Definition at line 809 of file MethodPDERS.cxx.
defines volume dimensions
Definition at line 483 of file MethodPDERS.cxx.
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static |
static pointer to this object
Definition at line 1184 of file MethodPDERS.cxx.
this is a dummy training: the preparation work to do is the construction of the binary tree as a pointer chain.
It is easier to directly save the trainingTree in the weight file, and to rebuild the binary tree in the test phase from scratch
Implements TMVA::MethodBase.
Definition at line 352 of file MethodPDERS.cxx.
update static this pointer
Definition at line 1191 of file MethodPDERS.cxx.
write training sample (TTree) to file
Definition at line 1170 of file MethodPDERS.cxx.
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Definition at line 179 of file MethodPDERS.h.
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private |
Definition at line 175 of file MethodPDERS.h.
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Definition at line 177 of file MethodPDERS.h.
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Definition at line 183 of file MethodPDERS.h.
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Definition at line 111 of file MethodPDERS.h.
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Definition at line 184 of file MethodPDERS.h.
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Definition at line 185 of file MethodPDERS.h.
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Definition at line 110 of file MethodPDERS.h.
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Definition at line 195 of file MethodPDERS.h.
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private |
Definition at line 193 of file MethodPDERS.h.
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Definition at line 147 of file MethodPDERS.h.
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Definition at line 198 of file MethodPDERS.h.
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Definition at line 197 of file MethodPDERS.h.
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Definition at line 200 of file MethodPDERS.h.
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Definition at line 192 of file MethodPDERS.h.
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Definition at line 191 of file MethodPDERS.h.
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Definition at line 190 of file MethodPDERS.h.
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Definition at line 202 of file MethodPDERS.h.
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Definition at line 187 of file MethodPDERS.h.
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Definition at line 201 of file MethodPDERS.h.
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Definition at line 182 of file MethodPDERS.h.
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Definition at line 181 of file MethodPDERS.h.
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Definition at line 178 of file MethodPDERS.h.
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Definition at line 146 of file MethodPDERS.h.
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