000			03046nam a2200289za04500
001			17666
008			050703s2011 gw eng d
020			_a9783642212802 99783642212802
082			_a006.3 _b223
100			_aZielesny, Achim. _eauthor. _934739
245			_aFrom Curve Fitting to Machine Learning _h[electronic resource]: _bAn Illustrative Guide to Scientific Data Analysis and Computational Intelligence / _cby Achim Zielesny.
300			_aXVI, 468p. 434 illus. _bonline resource.
490			_aIntelligent Systems Reference Library
490			_x-1868-4394 ; _v-18
505			_aIntroduction -- Curve Fitting -- Clustering -- Machine Learning -- Discussion -- CIP - Computational Intelligence Packages.
520			_aThe 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 clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence All topics are completely demonstrated with the aid of the commercial computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with Mathematica's programming language on top of Mathematica's algorithms. CIP is open-source so the detailed code of every method is freely accessible. All examples and applications shown throughout the book may be used and customized by the reader without any restrictions.
650			_aEngineering. _996
650			_aArtificial intelligence. _933648
650			_aEngineering. _996
650			_aArtificial Intelligence (incl. Robotics). _923200
650			_933564 _aAPPL.MATHEMATICS./ COMPUTATIONAL METHODS OF ENGINNEERING.
650			_934018 _aENGINEERING MATHEMATICS
650			_933763 _aCOMPUTATIONAL INTELIGENCE
710			_aSpringerLink (Online service) _9111
856			_uhttp://springer.escuelaing.metaproxy.org/book/10.1007/978-3-642-21280-2 _yir a documento _qURL
942			_2ddc _cCF
999			_c14291 _d14291