Evaluation and Optimization of the Effectiveness of Science Popularization Resources Using a Multi-Model Machine Learning Approach Combining Entropy Weight, XGBoost, and SHAP

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Evaluation and Optimization of the Effectiveness of Science Popularization Resources Using a Multi-Model Machine Learning Approach Combining Entropy Weight, XGBoost, and SHAP
Συγγραφείς: Wu, Yuju, Cai, Xiaoying, Zhang, Zhe
Πηγή: 2026 International Conference on Computational Intelligence and Machine Learning (CIML) Computational Intelligence and Machine Learning (CIML), 2026 International Conference on. :596-607 Mar, 2026
Relation: 2026 International Conference on Computational Intelligence and Machine Learning (CIML)
Βάση Δεδομένων: IEEE Xplore Digital Library
Περιγραφή
ISBN:9798331582821
9798331582838
DOI:10.1109/CIML69155.2026.11692634