Emerging Paradigms in Machine Learning

• Corporate Author: SpringerLink (Online service)
• Other Authors: Ramanna, Sheela (Editor), Jain, Lakhmi C. (Editor), Howlett, Robert J. (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: Smart Innovation, Systems and Technologies, 13
• Subjects: Engineering.; Artificial intelligence.; Computational intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).

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...

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.