IMPROVE BANK CUSTOMER PROFILING USING MODIFIED K-MEANS CLUSTERING
RAMYA M
, NIVETHA T S , RAMYA P
credit card customers analysis, data mining. data analysis , modified k means, denstity statistical
In today’s competitive markets for a successful business it is essential to satisfy the desires and preferences of customers. As the data grows enormously in banking and financing sectors, data analytics plays an important role in prediction and statistics. Banking sector provides different kinds of services in which this project focuses on credit card distribution. There are various types of customers who have different types of interest such as shopping, dining, exploring new places and so on. The banks also provide a varied number of credit cards with more number of specific services. This project focuses on finding the interest of each customer by performing data analytics on their previous usage data available in bank. The outlier detection is done using DENSAT algorithm to remove outliers. Then the clustering is done using Modified K-means clustering algorithm. Classification of the clustered customers is done using Support Vector Machine algorithm. Thus, the customers are classified into three groups a
"IMPROVE BANK CUSTOMER PROFILING USING MODIFIED K-MEANS CLUSTERING", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.353 - 358, May-2022, Available :https://ijsdr.org/papers/IJSDR2205067.pdf
Volume 7
Issue 5,
May-2022
Pages : 353 - 358
Paper Reg. ID: IJSDR_200373
Published Paper Id: IJSDR2205067
Downloads: 000347228
Research Area: Computer Engineering
Country: Madurai, Tamil Nadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
