Overview

Full Product Details

9781558604032

Table of Contents

Reviews

I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners. --Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University

""I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners."" --Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University

I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners. --Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University

Author Information

Sholom M. Weiss is a professor of computer science at Rutgers University and the author of dozens of research papers on data mining and knowledge-based systems. He is a fellow of the American Association for Artificial Intelligence, serves on numerous editorial boards of scientific journals, and has consulted widely on the commercial application of advanced data mining techniques. He is the author, with Casimir Kulikowski, of Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems, which is also available from Morgan Kaufmann Publishers. Nitin Indurkhya is on the faculty at the Basser Department of Computer Science, University of Sydney, Australia. He has published extensively on Data Mining and Machine Learning and has considerable experience with industrial data-mining applications in Australia, Japan and the USA.

Tab Content 6

Customer Reviews

Recent Reviews

Countries Available