Researchon Classification Techniques in Data Mining
O.Bhaskaru1, M.Sree Devi2
1O. Bhaskaru, Research Scholar, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Guntur District, Vaddeswaram, Andhra Pradesh, India.
2Dr. M. Sree Devi, Professor, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Guntur District, vaddeswaram, Andhra Pradesh, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 July 2019 | PP: 357-361 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F10720486S419/19©BEIESP | DOI: 10.35940/ijitee.F1072.0486S419
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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: Data Mining means a procedure to extracting the information out of large data. Data mining approaches includes classification, association rule, clustering, etc. Data mining is applied in four stages such as data sources, data extrapolation / gathering, modeling and deploying modules. Classification is a method in data mining to predict the group membership of data instances. It’s an method useful in data mining with vast applications for classifying the different types of data used in almost every fields. Classification is giving a class label to in determine set of cases. In this survey, we would like discuss Bayesian classification, rules based classification, Decision trees &neural network.
Keywords: Data Mining, Classification, Bayesian, Decision Trees, Neural Network.
Scope of the Article: Classification