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Introduction to Data Mining by Michael Steinbach, Vipin Kumar and Pang-Ning Tan (2005, Hardcover)

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About this product

Product Information

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

Product Identifiers

Publisher
Pearson Education
ISBN-10
0321321367
ISBN-13
9780321321367
eBay Product ID (ePID)
43742605

Product Key Features

Author
Vipin Kumar, Pang-Ning Tan, Michael Steinbach
Publication Name
Introduction to Data Mining
Format
Hardcover
Language
English
Publication Year
2005
Type
Textbook
Number of Pages
792 Pages

Dimensions

Item Length
9.4in
Item Height
1.6in
Item Width
7.7in
Item Weight
42.1 Oz

Additional Product Features

Lc Classification Number
Qa76.9.D343t35 2005
Table of Content
1 Introduction 1.1 What is Data Mining? 1.2 Motivating Challenges 1.3 The Origins of Data Mining 1.4 Data Mining Tasks 1.5 Scope and Organization of the Book 1.6 Bibliographic Notes 1.7 Exercises 2 Data 2.1 Types of Data 2.2 Data Quality 2.3 Data Preprocessing 2.4 Measures of Similarity and Dissimilarity 2.5 Bibliographic Notes 2.6 Exercises 3 Exploring Data 3.1 The Iris Data Set 3.2 Summary Statistics 3.3 Visualization 3.4 OLAP and Multidimensional Data Analysis 3.5 Bibliographic Notes 3.6 Exercises 4 Classification: Basic Concepts, Decision Trees, and Model Evaluation 4.1 Preliminaries 4.2 General Approach to Solving a Classification Problem 4.3 Decision Tree Induction 4.4 Model Overfitting 4.5 Evaluating the Performance of a Classifier 4.6 Methods for Comparing Classifiers 4.7 Bibliographic Notes 4.8 Exercises 5 Classification: Alternative Techniques 5.1 Rule-Based Classifier 5.2 Nearest-Neighbor Classifiers 5.3 Bayesian Classifiers 5.4 Artificial Neural Network (ANN) 5.5 Support Vector Machine (SVM) 5.6 Ensemble Methods 5.7 Class Imbalance Problem 5.8 Multiclass Problem 5.9 Bibliographic Notes 5.10 Exercises 6 Association Analysis: Basic Concepts and Algorithms 6.1 Problem Definition 6.2 Frequent Itemset Generation 6.3 Rule Generation 6.4 Compact Representation of Frequent Itemsets 6.5 Alternative Methods for Generating Frequent Itemsets 6.6 FP-Growth Algorithm 6.7 Evaluation of Association Patterns 6.8 Effect of Skewed Support Distribution 6.9 Bibliographic Notes 6.10 Exercises 7 Association Analysis: Advanced Concepts 7.1 Handling Categorical Attributes 7.2 Handling Continuous Attributes 7.3 Handling a Concept Hierarchy 7.4 Sequential Patterns 7.5 Subgraph Patterns
Copyright Date
2006
Target Audience
College Audience
Topic
Databases / Data Warehousing, Databases / Data Mining
Lccn
2005-008721
Dewey Decimal
006.3/12
Dewey Edition
22
Illustrated
Yes
Genre
Computers

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Most relevant reviews

5 out of 5 stars
by BBl69Q-MRou@Del...Nov 01, 2012
Great book for beginning with data mining
It is a great book. This my first time studying Data Mining, and most of topics are easy to understand. A few other I have to look for more information on Internet, but I think that's ok. It is important to mention that as its name mentions, it is an introduction of this topic; so, don't expect details about behavior algorithms. Authors explains in detail only a few algorithms. Maybe most popular/interesting ones.
5 out of 5 stars
by zhayu01Aug 23, 2016
Very good service
The service is very good. They shipped the book very fast and the book quality is satisfactory.
Verified purchase: Yes | Condition: New
5 out of 5 stars
by ibanez_6483Sep 24, 2012
Great product, very informative
Great book that gives a broad view of the subject of data mining. Plenty of examples and well written.

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