Review of Data Mining Classification Techniques
Journal Title: Bonfring International Journal of Software Engineering and Soft Computing - Year 2019, Vol 9, Issue 2
Abstract
A Classification is one the most valuable critical techniques. In huge information Classification procedures is helpful to deal with substantial measure of information. Orders are utilized to foresee straight out class names. Order models is utilized to the grouping recently accessible information into a class name. Characterization is the way toward finding an a model that depicts and The recognizes information classes or ideas. Order strategies can be handle both on numerical and all out characteristics. Developing quick and precise classifiers for vast informational indexes is the critical undertaking in information mining and learning revelation. Order predicts clear cut class marks and The groups information dependent on the preparation set. Characterization is the two stages forms. In this paper we speak to an investigation of different information mining characterization strategies like Decision Tree, K- Nearest Neighbor, Support Vector Machines, Naive Bayesian Classifiers, and Neural Networks.
Authors and Affiliations
Gowtham S, Karuppusamy S
Keywords
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- EP ID EP587727
- DOI 10.9756/BIJSESC.9013
- Views 117
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