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Learning from Data: Cleft Lip and Palate Patients in the West Coast of Sabah by Omar, Z A; Chin, S N; Hamzah, Norhafiza; Yassin, Fouziah is a Physics and Astronomy article available to read on EtoBox.

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## Abstract Analysing data can be quite a challenge sometimes due to the nature of the data and the vast options of methods and techniques that can be used on the data. In this study, for example, a six years Cleft Lip and Palate dataset were gathered on these patients’ conditions in the quest to identify the contributing factors for a successful pre-graft orthodontic treatment. The challenges faced was in the small number of datasets and imbalance sample class. Therefore, this study had taken a step back and tried to approach the dataset with a combination of unsupervised and supervised learning methods to tackle the challenges by incorporating clustering - for testing records creation and; resampling - for balancing sample class. We also observed if the auto-created testing records are replaceable with the manually selected testing records by looking at the performances of the classification models. Based on the feature that was selected, k-Means and PAM were implemented as the clustering algorithm using the Euclidean formula as the distance measure. Resampling was done using SMOTE and Random Forest as the classification model. When the comparison was done on the models, the ones

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Author

Omar, Z A; Chin, S N; Hamzah, Norhafiza; Yassin, Fouziah

Publisher

Institute of Physics; IOP Publishing (ISSN 1742-6588)

Published

2019

Language

EN

Field

Physics and Astronomy (Physical Sciences)