Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods

Tuğba Tuğ Karoğlu; Hayrettin Okut

doi:10.17776/csj.544639

EN

Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods

Abstract

The purpose of this study is to classify the data set which is created by taking students who placed to universities from 81 provinces, in accordance with Undergraduate Placement Examination between the years 2010-2013 in Turkey, with Bagging and Boosting methods which are Ensemble algorithms. The data set which is used in the study was taken from the archives of Turk-Stat. (Turkish Statistical Institute) and OSYM (Assessment, Selection and Placement Center) and MATLAB statistical software program was used. In order to evaluate Bagging and Boosting classification performances better, the success rates of the students were grouped into two groups. According to this, the provinces that were above the average were coded as 1, and the provinces below the average were coded as 0 and dependent variables were created. The Bagging and Boosting ensemble algorithms were run accordingly. In order to evaluate the prediction abilities of the Bagging and Boosting algorithms, the data set was divided into training and testing. For this purpose, while the data between 2010-2012 yearrs were used as training data, the data of the year 2013 were used as testing data. Accuracy, precision, recall and f-measure were used to demonstrate the performance of the methods in the study. As a result, the performance in consequence of "Bagging” and “Boosting” methods were compared. According to this; it was determined that in all performance measure marginally “Boosting” method produced better results than the “Bagging” method.

Keywords

AdaBoost,Bagging,Boosting,Ensemble Model

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Tuğba Tuğ Karoğlu ^*
0000-0002-7197-0747
Türkiye

Hayrettin Okut
0000-0003-4084-8404
United States

Publication Date

March 22, 2020

Submission Date

March 26, 2019

Acceptance Date

January 21, 2020

Published in Issue

Year 2020 Volume: 41 Number: 1

DOI

https://doi.org/10.17776/csj.544639

IZ

https://izlik.org/JA66DG68UU

Cite

RIS / Bibtex

APA

Tuğ Karoğlu, T., & Okut, H. (2020). Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods. Cumhuriyet Science Journal, 41(1), 93-105. https://doi.org/10.17776/csj.544639

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A comparative study of ensemble methods in the field of education: Bagging and Boosting algorithms

International Journal of Assessment Tools in Education

https://doi.org/10.21449/ijate.1167705

Öz

Classification of the placement success in the undergraduate placement examination according to decision trees with bagging and boosting methods

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Performance Analysis of Combination of CNN-based Models with Adaboost Algorithm to Diagnose Covid-19 Disease

A comparative study of ensemble methods in the field of education: Bagging and Boosting algorithms