Cost Learning Network for Imbalanced Classification
Journal
Proceedings - 25th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2020
Pages
47-51
Date Issued
2020
Author(s)
Tu C.-Y
Abstract
This paper proposes a method to improve the performance of imbalanced classification via reinforcement learning and cost-sensitive learning. Since the cost information is usually unavailable for cost-sensitive learning, we incorporate reinforcement learning to optimize the specified metric by adjusting the cost-matrix for the underlying cost-sensitive classifiers. Our experiment results show that, with the learned cost-matrix, the cost-sensitive classifiers can achieve better performance on several benchmark imbalanced data sets. ? 2020 IEEE.
Subjects
Benchmarking; Classification (of information); Learning systems; Cost information; Cost learning; Cost matrices; Cost-sensitive; Cost-sensitive learning; Imbalanced classification; Imbalanced Data-sets; Reinforcement learning
Type
conference paper