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I - Multivariate Classification and Machine Learning in HEP

<!--HTML-->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 regulari...

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Detalles Bibliográficos
Autor principal: KECK, Thomas
Lenguaje:eng
Publicado: 2016
Materias:
Acceso en línea:http://cds.cern.ch/record/2135801
Descripción
Sumario:<!--HTML-->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.