Introduction to data mining / Pang-Ning Tan...[et al.].

"As with the first edition, the second edition of the book provides a comprehensive introduction to data mining and is designed to be accessible and useful to students, instructors, researchers, and professionals. Areas covered include data preprocessing, predictive modeling, association analysis, cluster analysis, anomaly detection, and avoiding false discoveries. The goal is to present fundamental concepts and algorithms for each topic, thus providing the reader with the necessary background for the application of data mining to real problems. features New - as a result of developments in the industry, the text contains a deeper focus on big data and Includes Chapter changes in response to these advances. New - This edition contains new and updated approaches to data mining, specifically among the anomaly detection section New - An additional final Chapter discusses statistical concepts in the context of data mining techniques, something not found in other textbooks Updated - The classification chapters have been significantly changed to reflect the latest information in the industry, including a new section on deep learning and updates to the advanced classification chapter."--