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IEEE/ICACT20260013 Slide.11        [Big Slide]       [YouTube]	Oral Presentation
	This slide describes the training setup used in our experiments. First, the dataset is split into eighty percent for training and twenty percent for testing to ensure unbiased performance evaluation. Next, cross-validation is applied on the training set to improve model reliability and to reduce the risk of overfitting. Finally, model performance is evaluated using accuracy, precision, recall, and F1-score, which are well-suited metrics for classification-based job recommendation tasks.

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