1. "A multi-label classification framework based on deep learning and chain classifiers" by Y. Zhang, L. Cheng, and L. Zhu, published in Neurocomputing in 2021.
  2. "Enhanced Classifier Chains for Multi-Label Classification Using Hybridized Feature Selection and Feature Weighting Techniques" by S. R. Sankar and S. K. Kopparthi, published in IEEE Access in 2020.
  3. "Multi-Label Classification Using A Bayesian Framework and A Hybrid Chain Algorithm" by S. Saha and S. Mondal, published in the Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) in 2020.
  4. "Multi-Label Classification Based on Ensemble Classifier Chain with Semi-Supervised Learning" by M. P. Thakur and V. K. Singh, published in the Proceedings of the 2019 International Conference on Intelligent Systems Design and Applications (ISDA) in 2019.
  5. "Multi-Label Classification Using Classifier Chains and Label Embeddings" by S. Saha and S. Mondal, published in the Proceedings of the 2019 International Conference on Computational Intelligence and Computing Research (ICCIC) in 2019.
对Classifier Chain的改进算法列举近三年的文献

原文地址: https://www.cveoy.top/t/topic/bAMp 著作权归作者所有。请勿转载和采集!

免费AI点我,无需注册和登录