Improved Clustering and Naïve Bayesian based Binary Decision tree with Bagging Approach
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - November Issue 2013 by IJCTT Journal|
|Volume-5 Issue-2 |
|Year of Publication : 2013|
|Authors :Medeswara Rao, Sudhir Tirumalasetty|
Medeswara Rao, Sudhir Tirumalasetty"Improved Clustering and Naïve Bayesian based Binary Decision tree with Bagging Approach"International Journal of Computer Trends and Technology (IJCTT),V5(2):84-90 November Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- Decision Trees provide an attractive classification scheme which is responsible for making reliable decisions and possibly interpret them. Bayesian averaging over Decision trees allows estimating on attributes to assess the class posterior distribution and estimates the chance of making misleading decisions. The clustering problem has actually been addressed in several contexts in plenty of disciplines; due to this problem experimental data needs to clean the data before applying the data mining techniques. In this paper a new framework is proposed by integrating decision tree based attribute selection for data clustering.
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Keywords :— Decision tree, Classifier, NaiveBayes.