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
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: Smart Innovation, Systems and Technologies, 13
• Subjects: Engineering.; Artificial intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-28699-5

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 DataA Rough Set Approach
• Roles Played by Bayesian Networks in Machine Learning: An Empirical Investigation.