Data Mining and Analysis

Fundamental Concepts and Algorithms

Mohammed J. Zaki, Wagner Meira, Jr

• Publisher: Cambridge University Press
• Year: 2014
• Print ISBN: 9780521766333
• eBook ISBN: 9781107776685
• Topic: Informatica
• Subtopic: Database

The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.

Table of contents

• Cover
• Half-title
• Title page
• Copyright information
• Table of contents
• Preface
• 1 Data Mining and Analysis
• Part One Data Analysis Foundations
• Part Two Frequent Pattern Mining
• Part Three Clustering
• Part Four Classification
• Index