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Talk1 h 5 min

I - Multivariate Classification and Machine Learning in HEP

Thomas KECK · CERN

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About

Traditional multivariate methods for classification (Stochastic Gradient Boosted Decision Trees and Multi-Layer Perceptrons) are explained in theory and practise using examples from HEP. General aspects of multivariate classification are discussed, in particular different regularisation techniques. Afterwards, data-driven techniques are introduced and compared to MC-based methods..

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The talk

  1. I - Multivariate Classification and Machine Learning in HEP 2016-02-29 · 1 h 5 min · CERN's player

Credits and licence

Institution
CERN
Department
inverted CSC
Speaker
Thomas KECK
Year
2016
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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