Abstract
Machine learning has become a prominent approach for prediction in many fields of endeavor, including education. Python and R have become leading software while different packages have been developed for the purpose of carrying out machine learning analysis with differences in functions in R. This paper explored the functional and empirical differences of two major machine learning packages in R to estimate metrics. This comparative study provides a comprehensive guide for leveraging machine learning packages in R, facilitating informed decision-making, and advancing the adoption of effective methodologies in data-driven research and application. Findings in this study ensure that researchers make informed decisions in their selection of packages for analysis and understand alternatives, simplifying the technicalities of algorithm for practical researchers.
Recommended Citation
Oyeniran, Daniel O.
(2024)
"Comparison of Machine Learning Packages in R: An Application with Open Dataset,"
Chinese/English Journal of Educational Measurement and Evaluation | 教育测量与评估双语期刊: Vol. 5:
Iss.
3, Article 9.
DOI: https://doi.org/10.59863/XXDQ4938
Available at:
https://www.ce-jeme.org/journal/vol5/iss3/9
Data set
DOI
https://doi.org/10.59863/XXDQ4938