preprintarXiv (Cornell University)Mar 4, 2007GREEN OA

TMVA - Toolkit for Multivariate Data Analysis

HAHoecker, A.PSP. SpeckmayerJSJ. StelzerTJTherhaag, J.VTvon Toerne, E.

Grand Accélérateur National d'Ions Lourds · Laboratoire d’Annecy de Physique des Particules

Indexed inarxivdatacite

Abstract

In high-energy physics, with the search for ever smaller signals in ever larger data sets, it has become essential to extract a maximum of the available information from the data. Multivariate classification methods based on machine learning techniques have become a fundamental ingredient to most analyses. Also the multivariate classifiers themselves have significantly evolved in recent years. Statisticians have found new ways to tune and to combine classifiers to further gain in performance. Integrated into the analysis framework ROOT, TMVA is a toolkit which hosts a large variety of multivariate classification algorithms. Training, testing, performance evaluation and application of all available classifiers…

Citation impact

655
total citations
FWCI
Percentile
References
15
Citations per year

Authors

27

Topics & keywords

Keywords
  • Multivariate statistics
  • Computer science
  • Boosting (machine learning)
  • Machine learning
  • Realisation
  • Multivariate analysis
  • Data mining
  • Gradient boosting
UN Sustainable Development Goals
  • Affordable and clean energy
No related works found for this paper.