Sep 23, 2021 · Human activity recognition is an imbalance classification problem in essence since various human actions may occur at different frequencies.
Abstract—Human activity recognition is an imbalance classifica- tion problem in essence since various human actions may occur at different frequencies.
Human activity recognition is an imbalance classification problem in essence since various human actions may occur at different frequencies.
Based on seven imbalanced activity datasets derived from localization data for person activity, statistical experimental results show that the proposed ...
Nov 15, 2022 · A dual-ensemble framework for class imbalanced datasets is constructed. Optimizing the base classifier for each sub-dataset in inner ensemble.
Missing: Activity | Show results with:Activity
Bagging, as a commonly-used class imbalance learning method, combines resampling techniques with ensemble learning to provide a strong classifier with high ...
Missing: Activity | Show results with:Activity
Evolutionary dual-ensemble class imbalance learning for human activity recognition. Y Guo, Y Chu, B Jiao, J Cheng, Z Yu, N Cui, L Ma. IEEE Transactions on ...
Evolutionary Dual-Ensemble Class Imbalance Learning for Human Activity Recognition. Human activity recognition is an imbalance classification problem in ...
Jan 2, 2023 · A heterogeneous ensemble is a group of classification models trained using various algorithms and combined to output an effective recognition.
May 9, 2024 · This paper aims to encapsulate the recent breakthroughs in imbalanced learning by providing an in-depth review of extant strategies to confront this issue.