2023
DOI: 10.14569/ijacsa.2023.0141054
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Research on the Application of Random Forest-based Feature Selection Algorithm in Data Mining Experiments

Huan Wang

Abstract: Handling high-dimensional big data presents substantial challenges for Machine Learning (ML) algorithms, mainly due to the curse of dimensionality that leads to computational inefficiencies and increased risk of overfitting. Various dimensionality reduction and Feature Selection (FS) techniques have been developed to alleviate these challenges. Random Forest (RF), a widely-used Ensemble Learning Method (ELM), is recognized for its high accuracy and robustness, including its lesser-known capability for effectiv… Show more

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