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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Machine Learning Paradigms - Artificial Immune Systems and their Applications in Software Personalization (Hardcover, 1st ed. 2017)
Loot Price: R4,216
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Machine Learning Paradigms - Artificial Immune Systems and their Applications in Software Personalization (Hardcover, 1st ed. 2017)
Series: Intelligent Systems Reference Library, 118
Expected to ship within 10 - 15 working days
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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.
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