A Study on WEKA Tool for Data Preprocessing, Classification and Clustering
Swasti Singhal1, Monika Jena2
1Swasti Singhal, Department of Computer Science and Engineering, Amity University, Noida (U.P), India.
2Monika Jena, Professor, Department of Computer Science and Engineering, Amity University, Noida (U.P), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 250-253 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0843052613/13©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: The basic principles of data mining is to analyze the data from different angle, categorize it and finally to summarize it. In today’s world data mining have increasingly become very interesting and popular in terms of all application. The need for data mining is that we have too much data, too much technology but don’t have useful information. Data mining software allows user to analyze data. This paper introduces the key principle of data pre-processing, classification, clustering and introduction of WEKA tool. Weka is a data mining tool. In this paper we are describing the steps of how to use WEKA tool for these technologies. It provides the facility to classify the data through various algorithms.
Keywords: Data Mining; Data Preprocessing, Classification, Cluster Analysis, Weka Tool Etc.
Scope of the Article: Clustering