Soft Computing for Knowledge Discovery: Introducing Cartesian Granule Features (The Springer International Series in Engineering and Computer Science)
| Author | : | |
| Rating | : | 4.45 (702 Votes) |
| Asin | : | 1461369479 |
| Format Type | : | paperback |
| Number of Pages | : | 326 Pages |
| Publish Date | : | 2017-02-03 |
| Language | : | English |
DESCRIPTION:
It focuses on knowledge representation, machine learning, and the key methodologies that make up the fabric of soft computing - fuzzy set theory, fuzzy logic, evolutionary computing, and various theories of probability (e.g. Parallels are drawn between this approach and other well known approaches (such as naive Bayes and decision trees) leading to equivalences under certain conditions. The approaches presented are further illustrated in a battery of both artificial and real-world problems. naïve Bayes and Bayesian networks, Dempster-Shafer theory, mass assignment theory, and others). In addition to describing many state-of-the-art soft computing approaches to knowledge discovery, the author introduces Cartesian granulefeatures and their corresponding learning algorithms as an intuitive approach to knowledge discovery. Knowledge discovery is an area of computer science that attempts to uncover interesting and useful patterns in data that permit a computer to perform a task autonomously or assist a human in performing a task more efficiently.Soft Computing for Knowledge Discovery provides a self-contained and systematic exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspect
Outstanding contribution to the field of knowledge discovery The author, James Shanahan is internationally renowned across a number of computing fields including AI, information retrieval, information access, linguistics, text/data mining and machine learning. Indeed his expertise is reflected in his already substantial and growing IP portfolio. The book quickly made it's mark leading to a substantial international speaking itinerary and it has directly influenced many new approaches, research and developments in sof