Machine Learning Paradigms (Record no. 12382)

MARC details
000 -LEADER
fixed length control field 04616nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-319-47194-5
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20211206140646.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 161026s2017 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319471945
040 ## - CATALOGING SOURCE
Transcribing agency AIKTC-KRRC
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title ENG
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC009000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sotiropoulos, Dionisios N.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Machine Learning Paradigms
Medium [electronic resource] :
Remainder of title Artificial Immune Systems and their Applications in Software Personalization /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2017.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 327 p. 71 illus., 18 illus. in color.
Other physical details | Binding - Card Paper |
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Intelligent Systems Reference Library,
International Standard Serial Number 1868-4394 ;
Volume/sequential designation 118
520 ## - SUMMARY, ETC.
Summary, etc. The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems. The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Engineering
9 (RLIN) 4622
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Computational Intelligence.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Artificial Intelligence.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tsihrintzis, George A.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783319471921
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783319471938
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783319836751
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Intelligent Systems Reference Library,
International Standard Serial Number 1868-4394 ;
Volume/sequential designation 118
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-319-47194-5">https://doi.org/10.1007/978-3-319-47194-5</a>
Public note Click here to access eBook in Springer Nature platform. (Within Campus only.)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
Source of classification or shelving scheme Dewey Decimal Classification

No items available.

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