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  • Student Performance Prediction Using A Cascaded Bi-level Feature Selection Approach

    Wokili Abdullahi, Mary Ogbuka Kenneth, Morufu Olalere
    16-28

    Article ID: 3534
    551  (Abstract) 143  (Download)

    Abstract:

    Features in educational data are ambiguous which leads to noisy features and curse of dimensionality problems. These problems are solved via feature selection. There are existing models for features selection. These models were created using either a single-level embedded, wrapperbased or filter-based methods. However single-level filter-based methods ignore feature dependencies and ignore the interaction... More

    2021-08-25
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