Compressive Study on Various Classification Techniques Used in Data Mining

Authors

  • Charan Singh Tejavath  Research Scholar of Sri Satya Sai University of Technology and Medical Sciences. Sehore, Madhya Pradesh , India
  • Dr. R. P. Singh  Research Supervisor for Sri Satya Sai University of Technology and Medical Sciences Sehore, Madhya Pradesh, India

Keywords:

Classification Technique, Decision Tree Induction, K Nearest Neighbor Classifier, Bayesian Network, and Rule Based Classification. C4.5, ID3, ANN, Naive Bayes, SVM

Abstract

Data Mining is a developing field which has pulled in an expansive number of data enterprises because of the colossal volume of data oversaw as of late. Productive data mining requires a decent comprehension of the data mining techniques to enhance business opportunity and to enhance the nature of administration gave. In light of such needs, this paper gives a survey of conventional classification techniques utilized for data mining. Classification is utilized to discover in which assemble every datum occasion is identified with a given dataset. It is utilized for ordering data into various classes as indicated by a few requirements. A few noteworthy sorts of classification calculations including C4.5, ID3, k-closest neighbor classifier, Naive Bayes, SVM, and ANN are utilized for classification. By and large, a classification system takes three methodologies Statistical, Machine Learning and Neural Network for classification. While considering these methodologies this paper gives a comprehensive review of various classification calculations and their highlights and confinements

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

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Volume 2, Issue 6, November-December-2017

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Research Articles

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How to Cite

[1]
Charan Singh Tejavath, Dr. R. P. Singh, " Compressive Study on Various Classification Techniques Used in Data Mining, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.1396-1405, November-December-2017.