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Reseach Article

Data Mining: Analysis and Comparative Study of Supervised Techniques

by Balar Khalid, Chaabita Rachid, Boumhamdi Mounir
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 41
Year of Publication: 2019
Authors: Balar Khalid, Chaabita Rachid, Boumhamdi Mounir
10.5120/ijca2019919300

Balar Khalid, Chaabita Rachid, Boumhamdi Mounir . Data Mining: Analysis and Comparative Study of Supervised Techniques. International Journal of Computer Applications. 178, 41 ( Aug 2019), 22-25. DOI=10.5120/ijca2019919300

@article{ 10.5120/ijca2019919300,
author = { Balar Khalid, Chaabita Rachid, Boumhamdi Mounir },
title = { Data Mining: Analysis and Comparative Study of Supervised Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2019 },
volume = { 178 },
number = { 41 },
month = { Aug },
year = { 2019 },
issn = { 0975-8887 },
pages = { 22-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number41/30809-2019919300/ },
doi = { 10.5120/ijca2019919300 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:52:47.440863+05:30
%A Balar Khalid
%A Chaabita Rachid
%A Boumhamdi Mounir
%T Data Mining: Analysis and Comparative Study of Supervised Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 41
%P 22-25
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining techniques are used more and more in the economic field. Such as the prediction of certain economic indicators, the discovery of hidden information, problems or finding problems in the industrial sector, as well as in relations with customers through the study of their data and behaviors to improve the cost-effectiveness of customer relationships or attract new customers. Data Mining techniques are classified into two categories: supervised and unsupervised. This paper focus only on the first techniques for solving Data Mining tasks such as: Decision Trees, Regression, Neural Networks and Support vector machines (SVM). The new approach has succeed in defining some new criteria for the evaluation process, and it has obtained valuable results based on what the technique is, the environment of using each techniques, the advantages and disadvantages of each technique, the consequences of choosing any of these techniques to extract hidden predictive information from large databases, and the methods of implementation of each technique. Finally, the paper has presented some valuable recommendations in this field.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Regression Decision Trees Neural Networks SVM Supervised learning techniques