On Certain Patterns of Self Help Group Data: Using Clustering Approach

B. U. Sajeev

ISBN 10: 3659556459 / ISBN 13: 9783659556456

Published by LAP LAMBERT Academic Publishing, 2014

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Databases are growing in size to a stage where traditional techniques for analysis and visualization of the data are breaking down. In this book, knowledge of cluster analysis is applied to a socially relevant problem in India - Self Help Group (SHG). SHG has emerged as one of the most important models of socioeconomic development endeavours, particularly those aimed at women's empowerment, livelihoods strengthening and poverty alleviation. Cluster analysis is used to evaluate the performance of SHG groups. K-Means and Fuzzy C-Means algorithms are used to evaluate the financial status, socioeconomic, loan pattern and financial inclusion of SHG members. New algorithms namely Modified K-Means, Modified Fuzzy C-Means and Hybrid of K-Means and Fuzzy C-Means is used to evaluate various parameters of SHG data. These algorithms are also used to study the impact analysis of financial inclusion through SHG bank linkage. Cluster analysis is found to be very efficient, easy and reliable tool than statistical methods in data analysis.

Seller Inventory # 9783659556456

Bibliographic Details

• Title: On Certain Patterns of Self Help Group Data: Using Clustering Approach
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2014
• Language: English
• ISBN 10: 3659556459
• ISBN 13: 9783659556456
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 11D millimeters 220 millimeters width by 150 millimeters height by 11 millimeters depth
• Weight: 268 grams

About this title

Synopsis

Databases are growing in size to a stage where traditional techniques for analysis and visualization of the data are breaking down. In this book, knowledge of cluster analysis is applied to a socially relevant problem in India – Self Help Group (SHG). SHG has emerged as one of the most important models of socioeconomic development endeavours, particularly those aimed at women’s empowerment, livelihoods strengthening and poverty alleviation. Cluster analysis is used to evaluate the performance of SHG groups. K-Means and Fuzzy C-Means algorithms are used to evaluate the financial status, socioeconomic, loan pattern and financial inclusion of SHG members. New algorithms namely Modified K-Means, Modified Fuzzy C-Means and Hybrid of K-Means and Fuzzy C-Means is used to evaluate various parameters of SHG data. These algorithms are also used to study the impact analysis of financial inclusion through SHG bank linkage. Cluster analysis is found to be very efficient, easy and reliable tool than statistical methods in data analysis.

About the Author

Dr.Sajeev B.U,MSc,MCA,M.Tech(CS),Ph.D with 25 years of experience in teaching and research. He is the receipient of Bharat Ratna Jawaharlal Nehru Gold Medal award instituted by [GEPRA],Chennai, for his outstanding service, achievement and contribution to education and research.His area of research include datamining, Fuzzy logics, Image processing