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From Curve Fitting to Machine Learning

The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers that allowed the execution of highly non-linear and increasingly complex data analysis procedures - methods that were completely unfeasible before. Non-linear curve fitting, clust...

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Detalles Bibliográficos
Autor principal: Zielesny, Achim
Lenguaje:eng
Publicado: Springer 2011
Materias:
Acceso en línea:http://cds.cern.ch/record/1414316
Descripción
Sumario:The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers that allowed the execution of highly non-linear and increasingly complex data analysis procedures - methods that were completely unfeasible before. Non-linear curve fitting, clustering and machine learning belong to these modern techniques which are a further step towards computational intelligence. The goal of this book is to provide an interactive and illustrative guide to these topics. It concentrates on the road from two dimensional curve fitting to multidimensional clus