Proposed model overall structure (IMAGE)
Caption
The first stage involves feature selection, where a Double Feature Selection method is applied to identify the most relevant and influential features for training the model.
In the second stage, the model is developed using an ensemble machine learning stacking approach by combining K-Nearest Neighbors and Gaussian Naive Bayes classifiers with a Random Forest classifier.
A final classifier is then produced by selecting the optimal features for each classifier at each stage.
Credit
THE JOURNAL OF ENGINEERING RESEARCH 2025;22:173–186
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License
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