ROOT 6.10/09 Reference Guide |
Analysis of Boosted Decision Trees.
Boosted decision trees have been successfully used in High Energy Physics analysis for example by the MiniBooNE experiment (Yang-Roe-Zhu, physics/0508045). In Boosted Decision Trees, the selection is done on a majority vote on the result of several decision trees, which are all derived from the same training sample by supplying different event weights during the training.
successive decision nodes are used to categorize the events out of the sample as either signal or background. Each node uses only a single discriminating variable to decide if the event is signal-like ("goes right") or background-like ("goes left"). This forms a tree like structure with "baskets" at the end (leave nodes), and an event is classified as either signal or background according to whether the basket where it ends up has been classified signal or background during the training. Training of a decision tree is the process to define the "cut criteria" for each node. The training starts with the root node. Here one takes the full training event sample and selects the variable and corresponding cut value that gives the best separation between signal and background at this stage. Using this cut criterion, the sample is then divided into two subsamples, a signal-like (right) and a background-like (left) sample. Two new nodes are then created for each of the two sub-samples and they are constructed using the same mechanism as described for the root node. The devision is stopped once a certain node has reached either a minimum number of events, or a minimum or maximum signal purity. These leave nodes are then called "signal" or "background" if they contain more signal respective background events from the training sample.
the idea behind the boosting is, that signal events from the training sample, that *end up in a background node (and vice versa) are given a larger weight than events that are in the correct leave node. This results in a re-weighed training event sample, with which then a new decision tree can be developed. The boosting can be applied several times (typically 100-500 times) and one ends up with a set of decision trees (a forest).
In this particular variant of the Boosted Decision Trees the boosting is not done on the basis of previous training results, but by a simple stochastic re-sampling of the initial training event sample.
applying an individual decision tree to a test event results in a classification of the event as either signal or background. For the boosted decision tree selection, an event is successively subjected to the whole set of decision trees and depending on how often it is classified as signal, a "likelihood" estimator is constructed for the event being signal or background. The value of this estimator is the one which is then used to select the events from an event sample, and the cut value on this estimator defines the efficiency and purity of the selection.
Definition at line 49 of file MethodDT.h.
Public Member Functions | |
MethodDT (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="") | |
the standard constructor for just an ordinar "decision trees" More... | |
MethodDT (DataSetInfo &dsi, const TString &theWeightFile) | |
constructor from Reader More... | |
virtual | ~MethodDT (void) |
destructor More... | |
void | AddWeightsXMLTo (void *parent) const |
const Ranking * | CreateRanking () |
void | DeclareCompatibilityOptions () |
options that are used ONLY for the READER to ensure backward compatibility More... | |
void | DeclareOptions () |
Define the options (their key words) that can be set in the option string. More... | |
void | GetHelpMessage () const |
Double_t | GetMvaValue (Double_t *err=0, Double_t *errUpper=0) |
returns MVA value More... | |
Int_t | GetNNodes () |
Int_t | GetNNodesBeforePruning () |
Double_t | GetPruneStrength () |
virtual Bool_t | HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets) |
FDA can handle classification with 2 classes and regression with one regression-target. More... | |
void | ProcessOptions () |
the option string is decoded, for available options see "DeclareOptions" More... | |
Double_t | PruneTree () |
prune the decision tree if requested (good for individual trees that are best grown out, and then pruned back, while boosted decision trees are best 'small' trees to start with. More... | |
void | ReadWeightsFromStream (std::istream &istr) |
void | ReadWeightsFromXML (void *wghtnode) |
void | SetMinNodeSize (Double_t sizeInPercent) |
void | SetMinNodeSize (TString sizeInPercent) |
Double_t | TestTreeQuality (DecisionTree *dt) |
void | Train (void) |
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 |
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) |
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 \[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \] 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 () |
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 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... | |
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... | |
Private Member Functions | |
void | Init (void) |
common initialisation with defaults for the DT-Method More... | |
Static Private Attributes | |
static const Int_t | fgDebugLevel = 0 |
Additional Inherited Members | |
Public Types inherited from TMVA::MethodBase | |
enum | EWeightFileType { kROOT =0, kTEXT } |
Public Types inherited from TObject | |
enum | { kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff } |
enum | { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) } |
enum | EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) } |
Static Public Member Functions inherited from TObject | |
static Long_t | GetDtorOnly () |
Return destructor only flag. More... | |
static Bool_t | GetObjectStat () |
Get status of object stat flag. More... | |
static void | SetDtorOnly (void *obj) |
Set destructor only flag. More... | |
static void | SetObjectStat (Bool_t stat) |
Turn on/off tracking of objects in the TObjectTable. More... | |
Public Attributes inherited from TMVA::MethodBase | |
Bool_t | fSetupCompleted |
const Event * | fTmpEvent |
Protected 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 | MakeClassSpecific (std::ostream &, const TString &="") 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::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 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 |
#include <TMVA/MethodDT.h>
TMVA::MethodDT::MethodDT | ( | const TString & | jobName, |
const TString & | methodTitle, | ||
DataSetInfo & | theData, | ||
const TString & | theOption = "" |
||
) |
the standard constructor for just an ordinar "decision trees"
Definition at line 129 of file MethodDT.cxx.
TMVA::MethodDT::MethodDT | ( | DataSetInfo & | dsi, |
const TString & | theWeightFile | ||
) |
constructor from Reader
Definition at line 157 of file MethodDT.cxx.
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virtual |
destructor
Definition at line 370 of file MethodDT.cxx.
Implements TMVA::MethodBase.
Definition at line 525 of file MethodDT.cxx.
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virtual |
Implements TMVA::MethodBase.
Definition at line 568 of file MethodDT.cxx.
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virtual |
options that are used ONLY for the READER to ensure backward compatibility
Reimplemented from TMVA::MethodBase.
Definition at line 247 of file MethodDT.cxx.
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virtual |
Define the options (their key words) that can be set in the option string.
Implements TMVA::MethodBase.
Definition at line 214 of file MethodDT.cxx.
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virtual |
Implements TMVA::IMethod.
Definition at line 563 of file MethodDT.cxx.
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inline |
Definition at line 97 of file MethodDT.h.
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inline |
Definition at line 96 of file MethodDT.h.
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inline |
Definition at line 91 of file MethodDT.h.
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virtual |
FDA can handle classification with 2 classes and regression with one regression-target.
Implements TMVA::IMethod.
Definition at line 182 of file MethodDT.cxx.
common initialisation with defaults for the DT-Method
Implements TMVA::MethodBase.
Definition at line 345 of file MethodDT.cxx.
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virtual |
the option string is decoded, for available options see "DeclareOptions"
Implements TMVA::MethodBase.
Definition at line 258 of file MethodDT.cxx.
Double_t TMVA::MethodDT::PruneTree | ( | ) |
prune the decision tree if requested (good for individual trees that are best grown out, and then pruned back, while boosted decision trees are best 'small' trees to start with.
Well, at least the standard "optimal pruning algorithms" don't result in 'weak enough' classifiers !!
Definition at line 408 of file MethodDT.cxx.
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virtual |
Implements TMVA::MethodBase.
Definition at line 543 of file MethodDT.cxx.
Implements TMVA::MethodBase.
Definition at line 533 of file MethodDT.cxx.
Definition at line 322 of file MethodDT.cxx.
Definition at line 333 of file MethodDT.cxx.
Double_t TMVA::MethodDT::TestTreeQuality | ( | DecisionTree * | dt | ) |
Definition at line 508 of file MethodDT.cxx.
Implements TMVA::MethodBase.
Definition at line 377 of file MethodDT.cxx.
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private |
Definition at line 126 of file MethodDT.h.
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private |
Definition at line 132 of file MethodDT.h.
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private |
Definition at line 122 of file MethodDT.h.
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private |
Definition at line 106 of file MethodDT.h.
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staticprivate |
Definition at line 134 of file MethodDT.h.
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private |
Definition at line 119 of file MethodDT.h.
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private |
Definition at line 112 of file MethodDT.h.
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private |
Definition at line 113 of file MethodDT.h.
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private |
Definition at line 114 of file MethodDT.h.
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private |
Definition at line 116 of file MethodDT.h.
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private |
Definition at line 118 of file MethodDT.h.
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private |
Definition at line 137 of file MethodDT.h.
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private |
Definition at line 124 of file MethodDT.h.
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private |
Definition at line 125 of file MethodDT.h.
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private |
Definition at line 123 of file MethodDT.h.
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private |
Definition at line 127 of file MethodDT.h.
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private |
Definition at line 110 of file MethodDT.h.
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private |
Definition at line 111 of file MethodDT.h.
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private |
Definition at line 108 of file MethodDT.h.
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private |
Definition at line 128 of file MethodDT.h.
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private |
Definition at line 129 of file MethodDT.h.
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private |
Definition at line 117 of file MethodDT.h.
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private |
Definition at line 130 of file MethodDT.h.