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Interactive Post Mining Association Rules using Cost Complexity Pruning and Ontologies KDD

by Ch. Raja Ramesh, K V V Ramana, K. Raghava Rao, C V Sastry
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 20
Year of Publication: 2013
Authors: Ch. Raja Ramesh, K V V Ramana, K. Raghava Rao, C V Sastry
10.5120/11694-6034

Ch. Raja Ramesh, K V V Ramana, K. Raghava Rao, C V Sastry . Interactive Post Mining Association Rules using Cost Complexity Pruning and Ontologies KDD. International Journal of Computer Applications. 68, 20 ( April 2013), 16-21. DOI=10.5120/11694-6034

@article{ 10.5120/11694-6034,
author = { Ch. Raja Ramesh, K V V Ramana, K. Raghava Rao, C V Sastry },
title = { Interactive Post Mining Association Rules using Cost Complexity Pruning and Ontologies KDD },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 20 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number20/11694-6034/ },
doi = { 10.5120/11694-6034 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:23.285781+05:30
%A Ch. Raja Ramesh
%A K V V Ramana
%A K. Raghava Rao
%A C V Sastry
%T Interactive Post Mining Association Rules using Cost Complexity Pruning and Ontologies KDD
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 20
%P 16-21
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In data mining, association rule mining is very strong and limited by the huge amount of delivered rules, because of these so many problems facing to implementation. To overcome these drawbacks, several methods were proposed in the literature such as item sets concise, redundancy reduction, and post processing. Based on statistical information by using these methods the extracted rules may not be useful for the user. Thus, it is crucial to help the decision-controller with an efficient post processing step in order to reduce the number of rules. In this paper we have implemented a new interactive approach using cost complexity pruning and filter discovered rules, by using this approach we have to reduce the tree size with minimum number of error of validation set.

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Index Terms

Computer Science
Information Sciences

Keywords

clustering classification and association rules knowledge discover database

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