Evaluation of Association Rules in Liver Disease Data using Analytical Hierarchy Process for Decision Making
Ramjeevan Singh Thakur

Ramjeevan Singh Thakur, Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal (M.P), India
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 455-460 | Volume-8 Issue-6, April 2019 | Retrieval Number: E3281038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In General, Association Rule Mining Techniques Generate a Pool of Rule with Low Minimum Support Value. But, finding some best and potential rules from the pool of generated rules is a complex problem and nowadays it is also on demand. The proposed decision making process is based on analytic hierarchy process and gives potential rules related to liver disease which may play crucial role in decision making. For determining best rules from pool of generated rules some important measures such as support, confidence, length of rule and presence of high relevant features in a rule are considered. ILPD liver disease data is used for generating association rules and determining some of the best rules from pool of rule.
Keyword: Analytic Hierarchy Process,Decision Making, Liver Disease Data, Rule Evaluation
Scope of the Article: Data Mining