This is an undergraduate introduction to data mining. The book doesn't go into details. It may be suitable for people who want to get a quick feel of the data mining field. People who need more details shall read more serious and comprehensive introductions. Overall I am giving 4 stars, because I li
Principles of Data Mining
β Scribed by Max Bramer
- Publisher
- Springer
- Year
- 2007
- Tongue
- English
- Leaves
- 353
- Series
- Undergraduate Topics in Computer Science
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will benefit readers of all levels, from those who use data mining via commercial packages, right through to academic researchers. The book aims to help the general reader develop the necessary understanding to use commercial data mining packages, and to enable advanced readers to understand or contribute to future technical advances. Includes exercises and glossary.
β¦ Table of Contents
Max Bramer - Principle of Data Mining (Springer,2007)......Page p0001.djvu
Front Matter......Page p0003.djvu
Legal Matter......Page p0004.djvu
Contents......Page p0005.djvu
Introduction to Data Mining......Page p0011.djvu
1 - Data for Data Mining......Page p0021.djvu
2 - Introduction to Classification: NaΓ―ve Bayes and Nearest Neighbourg......Page p0033.djvu
3 - Using Decision Trees for Classification......Page p0051.djvu
4 - Decision Tree Induction: Using Entropy for Attribute Selction......Page p0061.djvu
5 - Decision Tree Induction: Using Frequency Tables for Attribute Selection......Page p0075.djvu
6 - Estimating the Predictive Accuracy of a Classifier......Page p0089.djvu
7 - Continuous Attributes......Page p0103.djvu
8 - Avoiding Overfitting of Decision Trees......Page p0129.djvu
9 - More About Entropy......Page p0145.djvu
10 - Inducing Modular Rules for Classification......Page p0165.djvu
11 - Measuring the Performance of a Classifier......Page p0183.djvu
12 - Association Rule Mining I......Page p0197.djvu
13 - Association Rule Mining II......Page p0213.djvu
14 - Clustering......Page p0231.djvu
15 - Text Mining......Page p0249.djvu
References......Page p0265.djvu
A - Essential Mathematics......Page p0267.djvu
B - Datasets......Page p0283.djvu
C - Sources of Further Information......Page p0303.djvu
D - Glossary and Notation......Page p0307.djvu
E - Solutions to Self-assessment Exercises......Page p0325.djvu
Index......Page p0349.djvu
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