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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 5 Issue 3 ijcatr05031011

IJCATR Volume 5 Issue 3

A Comparative Study of Various Data Mining Techniques: Statistics, Decision Trees and Neural Networks

Balar Khalid Naji Abdelwahab
10.7753/IJCATR0503.1011
keywords : Data mining, Statistics, Logistic Regression, Decision Trees and Neural Networks.

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In this paper we focus on some techniques for solving data mining tasks such as: Statistics, Decision Trees and Neural Networks. 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.
@artical{b532016ijcatr05031011,
Title = "A Comparative Study of Various Data Mining Techniques: Statistics, Decision Trees and Neural Networks",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="3",
Pages ="172 - 175",
Year = "2016",
Authors ="Balar Khalid Naji Abdelwahab"}
  • The paper proposes a comparative study of three techniques Data Mining.
  • Statistical techniques are used to discover patterns and build predictive models.
  • The neural networks are powerful mathematical models suitable for almost all data mining.
  • The Decision trees can naturally handle all types of variables, even with missing values.
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