CFP last date
22 July 2024
Reseach Article

Loan Application Approval using Meta Classifier

Published on September 2014 by B.rohit, K.p. Supreethi
National Conference on Advances in Technology and Applied Sciences
Foundation of Computer Science USA
NCATAS - Number 1
September 2014
Authors: B.rohit, K.p. Supreethi

B.rohit, K.p. Supreethi . Loan Application Approval using Meta Classifier. National Conference on Advances in Technology and Applied Sciences. NCATAS, 1 (September 2014), 34-37.

author = { B.rohit, K.p. Supreethi },
title = { Loan Application Approval using Meta Classifier },
journal = { National Conference on Advances in Technology and Applied Sciences },
issue_date = { September 2014 },
volume = { NCATAS },
number = { 1 },
month = { September },
year = { 2014 },
issn = 0975-8887,
pages = { 34-37 },
numpages = 4,
url = { /proceedings/ncatas/number1/17947-1609/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 National Conference on Advances in Technology and Applied Sciences
%A B.rohit
%A K.p. Supreethi
%T Loan Application Approval using Meta Classifier
%J National Conference on Advances in Technology and Applied Sciences
%@ 0975-8887
%N 1
%P 34-37
%D 2014
%I International Journal of Computer Applications

A Meta Classifier in this approach is used for the approval of Loan application, as a Data mining classification tool to support Business operations in a very secure way. The goal of designing a Meta classifier system is to achieve the best possible classification performance for the task of effective decision making. This Meta classifier is the combination of Naïve Bayesian classifier, K-Nearest Neighbor and Fuzzy Set approach. This classifier focuses on combination schemes of multiple classifiers to achieve better classification performance than that obtained by individual models, which in turn is used in providing loans to the customers by verifying the various details relating to the loan such as amount of loan, lending rate, loan term, type of property, income and credit history of the customer etc. The Meta Classifier helps in analyzing the involvement of risk and behavior of the customers by distinguishing borrowers who repay loans promptly from those who don't, hence reducing the loss of revenue.

  1. Jiawei Han, Micheline Kamber, Jian Pei, Data Mining concepts and techniques 3rd ed. , ISBN 978-0-12-381479-1, 2012.
  2. S. Rajasekaran, G. A. Vijayalakshmi Pai, Neural Networks, Fuzzy Logic, and Genetic Algorithms. ISBN- 978-81-203-2186-1.
  3. M. Srinivas, K. P. Supreethi, E. V. Prasad, Efficient text classification using best feature selection and combination of methods. Springer BerlinHeidelberg 2009.
  4. P´adraig Cunningham and Sarah Jane Delany "k-Nearest Neighbor Classi?ers". UCD-CSI-2007-4.
  5. Ricardas Mileris, Estimation of loan applicants default probability applying discriminant analysis and simple bayesian classifier, ECONOMICS AND MANAGEMENT: 2010. 15, ISSN 1822-6515.
  6. Is?k Biçer1, Deniz Sevis2, Taner Bilgiç1, Bayesian Credit Scoring Model with Integration of Expert Knowledge and customer data. Izmir University of Economics, Turkey, 2010. ISBN 978-9955-28-598-4.
  7. Gongde Guo and Daniel Neagu "Similarity-based Classifier Combination for Decision Making" Member, IEEE. SMCC-05-06-0125.
  8. Rujuta Shinde, Priya Vaghurdekar, Prof. Santaji Shinde. Delibration of Data Mining in Banking, IJERT Vol-I Issue 8, October-2012.
  9. Loan Data Sets by "Lending Club". https://www. lendingclub. com/info/download-data. action.
  10. T. K. Ho, J. J. Hull and S. N. Srihari. "Decision Combination in Multiple Classifier Systems". IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 16, Issue 1, pp. 66 – 75, 1994.
  11. L. Xu, A. Krzyzak, and C. Suen. "Methods of Combination Multiple Classifiers and Their Applications to Handwritten Recognition". IEEE Transactions on Systems, Man and Cybernetics, SMC-22(3):418-435, May/June 1992.
  12. LJUPC?O TODOROVSKI, SA?SO D?ZEROSKI "Combining Classifiers with Meta Decision Trees" Machine Learning, 50, 223–249, 2003
Index Terms

Computer Science
Information Sciences


Meta Classifier Naïve Bayesian Classifier K- Nearest Neighbor Fuzzy Set Theory