Machine Learning Paradigms
Springer International Publishing (Verlag)
978-3-319-47192-1 (ISBN)
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.
Introduction.- Machine Learning.- The Class Imbalance Problem.- Addressing the Class Imbalance Problem.- Machine Learning Paradigms.- Immune System Fundamentals.- Artificial Immune Systems.- Experimental Evaluation of Artificial Immune System-based Learning Algorithms.- Conclusions and Future Work.
Erscheinungsdatum | 16.11.2016 |
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Reihe/Serie | Intelligent Systems Reference Library |
Zusatzinfo | XVI, 327 p. 71 illus., 18 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Technik | |
Schlagworte | artificial immune systems • Artificial Intelligence • artificial intelligence (incl. robotics) • Computational Intelligence • Engineering • Engineering: general • Immune Systems • Intelligent Systems • machine learning • pattern recognition • Robotics |
ISBN-10 | 3-319-47192-9 / 3319471929 |
ISBN-13 | 978-3-319-47192-1 / 9783319471921 |
Zustand | Neuware |
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