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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Clustering Methods for Credit Card using Bayesian rules based on K-means classification

Author 1: S Jessica Saritha
Author 2: Prof. P.Govindarajulu
Author 3: K. Rajendra Prasad
Author 4: S.C.V. Ramana Rao
Author 5: C.Lakshmi

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2010.010416

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 4, 2010.

  • Abstract and Keywords
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Abstract: K-means clustering algorithm is a method of cluster analysis which aims to partition n observations into clusters in which each observation belongs to the cluster with the nearest mean. It is one of the simplest unconfirmed learning algorithms that solve the well known clustering problem. It is similar to the hope maximization algorithm for mixtures of Gaussians in that they both attempt to find the centers of natural clusters in the data. Bayesian rule is a theorem in probability theory named for Thomas Bayesian. It is used for updating probabilities by finding conditional probabilities given new data. In this paper, K-mean clustering algorithm and Bayesian classification are joint to analysis the credit card. The analysis result can be used to improve the accuracy.

Keywords: Clusters, Probability, K-Means, Thomas Bayesian rule, Credit Card, attributes, banking.

S Jessica Saritha, Prof. P.Govindarajulu, K. Rajendra Prasad, S.C.V. Ramana Rao and C.Lakshmi, “Clustering Methods for Credit Card using Bayesian rules based on K-means classification ” International Journal of Advanced Computer Science and Applications(IJACSA), 1(4), 2010. http://dx.doi.org/10.14569/IJACSA.2010.010416

@article{Saritha2010,
title = {Clustering Methods for Credit Card using Bayesian rules based on K-means classification },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2010.010416},
url = {http://dx.doi.org/10.14569/IJACSA.2010.010416},
year = {2010},
publisher = {The Science and Information Organization},
volume = {1},
number = {4},
author = {S Jessica Saritha and Prof. P.Govindarajulu and K. Rajendra Prasad and S.C.V. Ramana Rao and C.Lakshmi}
}


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