18-22 January 2016
UTFSM, Valparaíso (Chile)
Chile/Continental timezone

Development of Machine Learning Tools in ROOT

19 Jan 2016, 14:00
UTFSM, Valparaíso (Chile)

UTFSM, Valparaíso (Chile)

Avenida España 1680, Valparaíso Chile
Oral Data Analysis - Algorithms and Tools Track 2


Lorenzo Moneta (CERN) Omar Andres Zapata Mesa (Metropolitan Institute of Technology)


ROOT, a data analysis framework, provides advanced statistical methods needed by the LHC experiments for analyzing their data. These include machine learning tools required for classification, regression and clustering. These methods are provided by the TMVA, a toolkit for multi-variate analysis within ROOT. We will present recent development in TMVA and new interfaces between ROOT and TMVA and other well known statistical tools based on R and Python. We will show a new modular design of TMVA, giving users a lot of flexibility, novel features for cross-validation, variable selection and parallelism.

Primary authors

Lorenzo Moneta (CERN) Omar Andres Zapata Mesa (Metropolitan Institute of Technology) Dr Sergei Gleyzer (University of Florida (US))

Presentation Materials


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