A Survey of Classification Techniques in Data Mining |
Author(s): |
| A.RAJARAJESWARI , NGM COLLEGE,POLLACHI; R.Malathi Ravindran, NGM COLLEGE,POLLACHI |
Keywords: |
| Decision Tree, k-Nearest Neighbor classifier, Neural Networks, Naive-Bayes Classification. |
Abstract |
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Classification is a model finding process that is used for portioning the data into different classes according to some constrains. The main goal is to accurately predict the class for each data. A classification analysis requires that the end-user know ahead of time how classes are defined. This paper focuses on a survey on various classification techniques that are most commonly used in data-mining. There are several classification mechanisms that can be used such as K-nearest neighbor, Bayesian network, Neural Networks, Decision Trees, Fuzzy Logic, Support Vector Machine, Boosting etc. This paper also deals with a study on some of these commonly used techniques that are being widely used. |
Other Details |
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Paper ID: IJSRDV2I3343 Published in: Volume : 2, Issue : 3 Publication Date: 01/06/2014 Page(s): 655-657 |
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