Browsing by Author "Tseng, Vincent Shin-Mu"

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Deep Discriminative Features Learning and Sampling for Imbalanced Data Problem
(2018-01-01)
Liu, Yi-Hsun
;
Liu, Chien-Liang
;
Tseng, Vincent Shin-Mu
;
資訊工程學系
;
工業工程與管理學系
The imbalanced data problem occurs in many application domains and is considered to be a challenging problem in machine learning and data mining. Most resampling methods for synthetic data focus on minority class without considering the data distribution of major classes. In contrast to previous works, the proposed method considers both majority classes and minority classes to learn feature embeddings and utilizes appropriate loss functions to make feature embedding as discriminative as possible. The proposed method is a comprehensive framework and different deep learning feature extractors can be utilized for different domains. We conduct experiments utilizing seven numerical datasets and one image dataset based on multiclass classification tasks. The experimental results indicate that the proposed method provides accurate and stable results.