AdaBoost Extensions for Cost-Sensitive Classification

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.

Autorentext

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.