Speaker
Dr
Joerg Stelzer
(DESY, Germany)
Description
At the dawn of LHC data taking, multivariate data analysis techniques
have become the core of many physics analyses. TMVA provides easy
access to sophisticated multivariate classifiers and is widely used to
study and deploy these for data selection. Beyond classification, most
multivariate methods in TMVA perform regression optimization which can
be used to predict data corrections, e.g. for calibration or shower
corrections. The tightening of the integration with ROOT provides a
common platform for discussion between the user community and the TMVA
devolopers. The talk gives an overview of the new features in TMVA
such as regression, multi-class classification and cathegorization,
the extented pre-processing capabilities, and planned further
developments.
Authors
Dr
Andreas Hoecker
(CERN, Switzerland)
Dr
Eckhard von Toerne
(Bonn University, Germany)
Dr
Helge Voss
(MPI Munich, Germany)
Jan Therhaag
(Bonn University, Germany)
Dr
Joerg Stelzer
(DESY, Germany)
Dr
Peter Speckmayer
(CERN, Switzerland)
