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:: Volume 26, Issue 1 (12-2021) ::
Andishe 2021, 26(1): 47-59 Back to browse issues page
Comparison of logistic regression with some machine learning methods in classifying data
Tayebeh Karami *, Muhyiddin Izadi, Mehrdad Niaparast
Abstract:   (1128 Views)
The subject of classification is one of the important issues in different sciences. Logistic regression is one of the statistical
methods to classify data in which the underlying distribution of the data is assumed to be known. Today, researchers in
addition to statistical methods use other methods such as machine learning in which the distribution of the data does not
need to be known. In this paper, in addition to the logistic regression, some machine learning methods including CART
decision tree, random forest, Bagging and Boosting of supervising learning are introduced. Finally, using four real data
sets, we compare the performance of these algorithms with respect to the accuracy measure.
Keywords: Decision Tree, Ensemble Learning, Random Forest, Supervised Learning.
Full-Text [PDF 376 kb]   (496 Downloads)    
Type of Study: Applicable | Subject: Special
Received: 2021/04/24 | Accepted: 2021/11/22 | Published: 2021/12/1
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karami T, Izadi M, Niaparast M. Comparison of logistic regression with some machine learning methods in classifying data. Andishe. 2021; 26 (1) :47-59
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Volume 26, Issue 1 (12-2021) Back to browse issues page
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