Data Cleaning in Medical Procurement Database: Performance Comparison of Data Mining Classification Algorithms for Tackling Missing Value

Amarawan Pentrakan; Arbee L. P. Chen

doi:10.55549/epstem.1357602

Conference Paper

Data Cleaning in Medical Procurement Database: Performance Comparison of Data Mining Classification Algorithms for Tackling Missing Value

Year 2023, Volume: 23, 26 - 33, 30.09.2023

Amarawan Pentrakan Arbee L. P. Chen

https://doi.org/10.55549/epstem.1357602

Abstract

Data cleaning is an important process for improving the quality of decision-making information. One of today's popular cleaning tools is data mining techniques. In this paper, we focused on using data mining classification algorithms to resolve missing values in medical purchasing databases. To serve this purpose, the predictive performance of four different classifiers: Decision Tree, Naïve Bayes, K-Nearest Neighbor, and Support Vector Machine (SVM) were compared in this study. We used 2,311 medical data records from procurement database in Thailand between July 2019 and December 2019 in the experimental process. We also discussed the function of feature selection and test options that support analysis to improve model performance. The results showed that the SVM algorithm outperforms with a maximum accuracy of 89.61%. Additionally, we discussed the strengths and weaknesses of these data mining techniques for data cleaning and future research.

Keywords

Data mining techniques , Classification algorithms , Medical procurement database , Missing values

References

Batt, S., Grealis, T., Harmon, O., & Tomolonis, P. (2020). Learning Tableau: A data visualization tool. The Journal of Economic Education, 51(3-4), 317-328.
Bouckaert, R. R. (2008). Bayesian network classifiers in weka for version 3-5-7. Artificial Intelligence Tools, 11(3), 369-387.
Browne, M. W. (2000). Cross-validation methods. Journal of Mathematical Psychology, 44(1), 108-132.
Chabot, C., Stolte, C., & Hanrahan, P. (2003). Tableau software. Tableau Software, 6.

Year 2023, Volume: 23, 26 - 33, 30.09.2023

Amarawan Pentrakan Arbee L. P. Chen

https://doi.org/10.55549/epstem.1357602

Abstract

References

Batt, S., Grealis, T., Harmon, O., & Tomolonis, P. (2020). Learning Tableau: A data visualization tool. The Journal of Economic Education, 51(3-4), 317-328.
Bouckaert, R. R. (2008). Bayesian network classifiers in weka for version 3-5-7. Artificial Intelligence Tools, 11(3), 369-387.
Browne, M. W. (2000). Cross-validation methods. Journal of Mathematical Psychology, 44(1), 108-132.
Chabot, C., Stolte, C., & Hanrahan, P. (2003). Tableau software. Tableau Software, 6.

There are 4 citations in total.

Details

Primary Language	English
Subjects	Software Testing, Verification and Validation
Journal Section	Articles
Authors	Amarawan Pentrakan Arbee L. P. Chen
Early Pub Date	September 9, 2023
Publication Date	September 30, 2023
Published in Issue	Year 2023 Volume: 23

Cite

APA	Pentrakan, A., & Chen, A. L. P. (2023). Data Cleaning in Medical Procurement Database: Performance Comparison of Data Mining Classification Algorithms for Tackling Missing Value. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 26-33. https://doi.org/10.55549/epstem.1357602