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Introduction to Data Mining
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eBay item number:285722602919
Item specifics
- Condition
- Release Year
- 2005
- Book Title
- Introduction to Data Mining
- ISBN
- 9780321321367
- Subject Area
- Computers
- Publication Name
- Introduction to Data Mining
- Item Length
- 9.4 in
- Publisher
- Pearson Education
- Subject
- Databases / Data Warehousing, Databases / Data Mining
- Publication Year
- 2005
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1.6 in
- Item Width
- 7.7 in
- Item Weight
- 42.1 Oz
- Number of Pages
- 792 Pages
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
Publication Name
Introduction to Data Mining
Format
Hardcover
Language
English
Subject
Databases / Data Warehousing, Databases / Data Mining
Publication Year
2005
Type
Textbook
Subject Area
Computers
Number of Pages
792 Pages
Dimensions
Item Length
9.4 in
Item Height
1.6 in
Item Width
7.7 in
Item Weight
42.1 Oz
Additional Product Features
LCCN
2005-008721
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
Dewey Decimal
006.3/12
Dewey Edition
22
Illustrated
Yes
Item description from the seller
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eBay item number:285722602919
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Most relevant reviews
- Nov 01, 2012
Great book for beginning with data mining
- Aug 23, 2016
Very good service
Verified purchase: YesCondition: NewSold by: vbkz
- Sep 24, 2012
Great product, very informative