Simulation of Various Classifications Results using WEKA
Shilpa Dhanjibhai Serasiya1, Neeraj Chaudhary2
1Ms. Shilpa Dhanjibhai Serasiya, M. Tech. Student, Department of Computer Science Engg., Rajasthan Collage of Engineering for Women, Jaipur (Rajasthan), India.
2Prof. Neeraj Choudhary, Reader, Department of CSE, Rajasthan Collage of Engineering for Women, Jaipur (Rajasthan), India.
Manuscript received on 18 August 2012 | Revised Manuscript received on 25 August 2012 | Manuscript published on 30 August 2012 | PP: 155-162 | Volume-1 Issue-3, August 2012 | Retrieval Number: C0295071312/2012©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 this paper, we focused on the construction of class association rules and classification model. In knowledge discovery process association rule mining and classification are two important techniques of data mining and widely used in various fields. In order to mine only rules that can be used for prediction, we modified the well known association rule mining algorithm – Apriori to handle user-defined input constraints. The paper tries to explain the basics of class association rule mining and classification through WEKA. This article presents how problems of classification and prediction can be solved using class association rules. In the simulation on WEKA, we have used selected classification techniques to propose the appropriate result from our training dataset. Thus, by using the simulated results, we suggest the classification using association rules.
Keywords: Association Rule, Class Association Rules, Classification, Data mining.
Scope of the Article: Classification