Principles of Data Mining

By: David J. Hand, Heikki Mannila, Padhraic Smyth

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Hardcover | 17 August 2001

At a Glance

Hardcover
578 Pages

Age
18+

Dimensions(cm)
0.1 x 0.1 x 0.1

Hardcover

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The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

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You Can Find This Book In

Non-Fiction Computing & I.T.Databases Data Mining Computer Programming & Software Development Algorithms & Data Structures Computer Science Mathematical Theory of Computation Information Technology General Issue Artificial Intelligence Machine Learning

Full Contents
List of Tables
List of Figures
Series Foreword
Preface
Introduction
Measurement and Data
Visualizing and Exploring Data
Data Analysis and Uncertainty
A Systematic Overview of Data Mining Algorithms
Models and Patterns
Score Functions for Data Mining Algorithms
Search and Optimization Methods
Descriptive Modeling
Predictive Modeling for Classification
Predictive Modeling for Regression
Data Organization and Databases
Finding Patterns and Rule
Retrieval by Content
Appendix: Random Variables
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

Principles of Data Mining

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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