AdaBoost Extensions for Cost-Sensitive Classification | A research under data mining classification

Ankit Desai

ISBN 10: 3659179493 / ISBN 13: 9783659179495

Published by LAP Lambert Academic Publishing, 2012

About this Item

AdaBoost Extensions for Cost-Sensitive Classification | A research under data mining classification | Ankit Desai | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659179495 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Bibliographic Details

• Title: AdaBoost Extensions for Cost-Sensitive Classification | A research under data mining classification
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659179493
• ISBN 13: 9783659179495
• Binding: Taschenbuch
• Condition: Neu
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book provides a review and a research of a special type of classification technique which is known as cost-sensitive data mining. Cost-sensitive data mining is an essential technique of data mining for applications like fraud-detection and loan-approval where the cost of misclassification of a sample is critical. It provides an overview of many algorithms which falls under this cluster. Proposed algorithms namely, CSExtension1, CSExtension2, CSExtension3, CSExtension4 and CSExtension5 are implemented and tested as an extension to data mining tool weka by the author of this book. These all algorithms provide adequate results for the parameters, cost-of-misclassificaiton and number of high cost errors. At the end, it gives new directions to its readers for unexplored areas in the same domain.

About the Author

Ankit Desai, is an Assistant Professor in Information Technology Department of Charotar University of Science and Technology. He pursued his B.E.(I.T.) from CIT, Changa in 2007 and M.Tech.(C.E., Gold Medalist) from DDU, Nadiad in 2012. His research interest includes, Algorithms, Data Mining, Software Refactoring, Open-Source and Info. Security.