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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Sensors and Materials, Volume 36, Number 4(2) (2024)
Copyright(C) MYU K.K.
pp. 1461-1471
S&M3611 Research Paper of Special Issue
https://doi.org/10.18494/SAM5029
Published: April 19 , 2024

An Alternative Method for Upgrading the Conventional Decision Tree Algorithm [PDF]

Suppakrit Kirdponpattara, Veera Boonjing, and Pitikhate Sooraksa

(Received February 21, 2024; Accepted March 19, 2024)

Keywords: decision tree, defect prediction, feature selection, hard disk drive manufacturing

Decision tree algorithms are widely used for solving classification and regression problems. Their popularity can be attributed to their transparent nature, simplicity, easy interpretability, faster classification speed, and strong decision rules. However, decision tree induction algorithms face various inherent and external limitations, such as overfitting, high sensitivity to noise and outliers, and instability with minimal data variations. In this study, we introduce an innovative approach to enhance traditional decision tree algorithms [e.g., Iterative Dichotomiser 3 (ID3), C4.5, and Classification and Regression Trees (CART)] by incorporating feature selection techniques. The proposed approach aims to enhance the accuracy and efficiency of decision tree models. Experiments were conducted on a real-world dataset of a hard disk drive (HDD) manufacturing process using the proposed approach. In comparison with a baseline where all features were utilized, the study highlighted a significant improvement in accuracy, indicating that the approach holds immense potential for optimizing decision tree algorithms and improving the HDD manufacturing process.

Corresponding author: Pitikhate Sooraksa


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Cite this article
Suppakrit Kirdponpattara, Veera Boonjing, and Pitikhate Sooraksa, An Alternative Method for Upgrading the Conventional Decision Tree Algorithm, Sens. Mater., Vol. 36, No. 4, 2024, p. 1461-1471.



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