Verfügbarkeit: Emerging paradigms in machine learning

Emerging paradigms in machine learning:

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Bibliographische Detailangaben
Weitere Verfasser:	Ramanna, Sheela (HerausgeberIn), Jain, L. C. 1946- (HerausgeberIn), Howlett, Robert J. (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Berlin Springer [2013]
Schriftenreihe:	Smart innovation, systems and technologies volume 13
Schlagworte:	Engineering Artificial intelligence Computational intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen Aufsatzsammlung
Online-Zugang:	BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online Ressource (XXII, 498 p)
ISBN:	9783642286995
DOI:	10.1007/978-3-642-28699-5

Internformat

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Datensatz im Suchindex

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adam_text	EMERGING PARADIGMS IN MACHINE LEARNING / : 2013 TABLE OF CONTENTS / INHALTSVERZEICHNIS 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 DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. EMERGING PARADIGMS IN MACHINE LEARNING / : 2013 ABSTRACT / INHALTSTEXT 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. DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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spellingShingle	Emerging paradigms in machine learning Smart innovation, systems and technologies Engineering Artificial intelligence Computational intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd
subject_GND	(DE-588)4193754-5 (DE-588)4143413-4
title	Emerging paradigms in machine learning
title_auth	Emerging paradigms in machine learning
title_exact_search	Emerging paradigms in machine learning
title_full	Emerging paradigms in machine learning Sheela Ramanna, Lakhmi C Jain, Robert J. Howlett (eds.)
title_fullStr	Emerging paradigms in machine learning Sheela Ramanna, Lakhmi C Jain, Robert J. Howlett (eds.)
title_full_unstemmed	Emerging paradigms in machine learning Sheela Ramanna, Lakhmi C Jain, Robert J. Howlett (eds.)
title_short	Emerging paradigms in machine learning
title_sort	emerging paradigms in machine learning
topic	Engineering Artificial intelligence Computational intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd
topic_facet	Engineering Artificial intelligence Computational intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen Aufsatzsammlung
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