Boosting
Author:
Affiliation:
1. Seminar für Statistik, ETH Zürich, Zürich, CH–8092, Switzerland
2. Department of Statistics, University of California, Berkeley, CA 94720‐3860, USA
Publisher
Wiley
Subject
Statistics and Probability
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.55
Reference35 articles.
1. Crytographic limitations on learning Boolean formulae and finite automata
2. The strength of weak learnability
3. Arcing classifier (with discussion and a rejoinder by the author)
4. Prediction Games and Arcing Algorithms
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites;Computers in Biology and Medicine;2024-05
2. A Method for Assigning Weight to the Assessment Indicators of Computational Thinking with XGBoost;2023 5th International Workshop on Artificial Intelligence and Education (WAIE);2023-09-28
3. Deep learning and ensemble deep learning for circRNA-RBP interaction prediction in the last decade: A review;Engineering Applications of Artificial Intelligence;2023-08
4. Ensemble species distribution modeling ofCulex tarsalis(Diptera: Culicidae) in the continental United States;Journal of Medical Entomology;2023-04-15
5. Improving insurers’ loss reserve error prediction: Adopting combined unsupervised-supervised machine learning techniques in risk management;The Journal of Finance and Data Science;2022-11
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