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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...

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Corporate Author: SpringerLink (Online service)
Other Authors: Ramanna, Sheela. (Editor, http://id.loc.gov/vocabulary/relators/edt), Jain, Lakhmi C. (Editor, http://id.loc.gov/vocabulary/relators/edt), Howlett, Robert J. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Smart Innovation, Systems and Technologies, 13
Subjects:
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.
Online Access:https://doi.org/10.1007/978-3-642-28699-5
Table of Contents:
  • 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.

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