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Using genetic algorithm in outlier detection for regression model
Joint Authors
Thabit, Hamsa M.
al-Jamal, Zakariyya Yahya
Source
al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah
Issue
Vol. 27, Issue 3 (30 Sep. 2018), pp.1-7, 7 p.
Publisher
University of Mosul College of Education for Pure Science
Publication Date
2018-09-30
Country of Publication
Iraq
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
Linear regression model is commonly used to analyze data from many fields.
Sometimes the data under research contains outliers, and it is important that these outliers be identified in the course of the correct statistical analysis.
In this article we used genetic algorithm (GA) with three type of objective functions,Akaike information criterion (AIC), Bayesian information criterion (BIC), and Hannan–Quinn information criterion (HQIC) to detect the problem of masking and swamping outliers in linear regression model .
Two well – known data sets have been studied and we conclude that GA doing-well in detection these type of outliers when using AIC and HQIC comparingwithBIC.
American Psychological Association (APA)
al-Jamal, Zakariyya Yahya& Thabit, Hamsa M.. 2018. Using genetic algorithm in outlier detection for regression model. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah،Vol. 27, no. 3, pp.1-7.
https://search.emarefa.net/detail/BIM-899651
Modern Language Association (MLA)
al-Jamal, Zakariyya Yahya& Thabit, Hamsa M.. Using genetic algorithm in outlier detection for regression model. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah Vol. 27, no. 3 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-899651
American Medical Association (AMA)
al-Jamal, Zakariyya Yahya& Thabit, Hamsa M.. Using genetic algorithm in outlier detection for regression model. al-Tarbiyah wa-al-Ilm : Majallat ilmiyah lil-Buhuth al-Ilmiyah al-Asasiyah. 2018. Vol. 27, no. 3, pp.1-7.
https://search.emarefa.net/detail/BIM-899651
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 6-7
Record ID
BIM-899651