E-Book, Englisch, 344 Seiten, eBook
Bramer Principles of Data Mining
2007
ISBN: 978-1-84628-766-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 344 Seiten, eBook
Reihe: Undergraduate Topics in Computer Science
ISBN: 978-1-84628-766-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Lower undergraduate
Autoren/Hrsg.
Weitere Infos & Material
Data for Data Mining.- to Classification: Na¨ive Bayes and Nearest Neighbour.- Using Decision Trees for Classification.- Decision Tree Induction: Using Entropy for Attribute Selection.- Decision Tree Induction: Using Frequency Tables for Attribute Selection.- Estimating the Predictive Accuracy of a Classifier.- Continuous Attributes.- Avoiding Overfitting of Decision Trees.- More About Entropy.- Inducing Modular Rules for Classification.- Measuring the Performance of a Classifier.- Association Rule Mining I.- Association Rule Mining II.- Clustering.- Text Mining.
