Cargando…

Emerging Paradigms in Machine Learning

This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Ramanna, Sheela (Editor ), Jain, Lakhmi C. (Editor ), Howlett, Robert J. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Smart Innovation, Systems and Technologies, 13
Temas:
Acceso en línea:Texto Completo

MARC

LEADER 00000nam a22000005i 4500
001 978-3-642-28699-5
003 DE-He213
005 20220119151216.0
007 cr nn 008mamaa
008 120730s2013 gw | s |||| 0|eng d
020 |a 9783642286995  |9 978-3-642-28699-5 
024 7 |a 10.1007/978-3-642-28699-5  |2 doi 
050 4 |a Q342 
072 7 |a UYQ  |2 bicssc 
072 7 |a TEC009000  |2 bisacsh 
072 7 |a UYQ  |2 thema 
082 0 4 |a 006.3  |2 23 
245 1 0 |a Emerging Paradigms in Machine Learning  |h [electronic resource] /  |c edited by Sheela Ramanna, Lakhmi C Jain, Robert J. Howlett. 
250 |a 1st ed. 2013. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XXII, 498 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Smart Innovation, Systems and Technologies,  |x 2190-3026 ;  |v 13 
505 0 |a From the content: Emerging Paradigms in Machine Learning: An Introduction -- Extensions of Dynamic Programming as a New Tool for Decision Tree Optimization -- Optimised information abstraction in granular Min/Max clustering -- Mining Incomplete Data-A Rough Set Approach -- Roles Played by Bayesian Networks in Machine Learning: An Empirical Investigation. 
520 |a This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.  Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary data streams are a key part of this book.   . 
650 0 |a Computational intelligence. 
650 0 |a Artificial intelligence. 
650 1 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence. 
700 1 |a Ramanna, Sheela.  |e editor.  |0 (orcid)0000-0003-4169-6115  |1 https://orcid.org/0000-0003-4169-6115  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Jain, Lakhmi C.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Howlett, Robert J.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783642287008 
776 0 8 |i Printed edition:  |z 9783642435744 
776 0 8 |i Printed edition:  |z 9783642286988 
830 0 |a Smart Innovation, Systems and Technologies,  |x 2190-3026 ;  |v 13 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-642-28699-5  |z Texto Completo 
912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)