Function Members (Methods)
public:
| virtual | ~QuickMVAProbEstimator() |
| void | AddEvent(Double_t val, Double_t weight, Int_t type) |
| static TClass* | Class() |
| static bool | compare(TMVA::QuickMVAProbEstimator::EventInfo e1, TMVA::QuickMVAProbEstimator::EventInfo e2) |
| Double_t | GetMVAProbAt(Double_t value) |
| virtual TClass* | IsA() const |
| TMVA::QuickMVAProbEstimator& | operator=(const TMVA::QuickMVAProbEstimator&) |
| TMVA::QuickMVAProbEstimator | QuickMVAProbEstimator(const TMVA::QuickMVAProbEstimator&) |
| TMVA::QuickMVAProbEstimator | QuickMVAProbEstimator(Int_t nMin = 40, Int_t nMax = 5000) |
| virtual void | ShowMembers(TMemberInspector& insp) const |
| virtual void | Streamer(TBuffer&) |
| void | StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b) |
Class Charts
Function documentation
Double_t GetMVAProbAt(Double_t value)
Well.. if it's fast is actually another question all together, merely it's a quick and dirty simple kNN approach to the 1-Dim signal/backgr. MVA distributions.
bool compare(TMVA::QuickMVAProbEstimator::EventInfo e1, TMVA::QuickMVAProbEstimator::EventInfo e2)
{return e1.eventValue < e2.eventValue;} QuickMVAProbEstimator(Int_t nMin = 40, Int_t nMax = 5000)
{ fLogger = new MsgLogger("QuickMVAProbEstimator");}