4 papers
Principal Component Analysis Based on T-norm Maximization
Xiang-Fei Yang, Yuan-Hai Shao, Chun-Na Li +2
Classical principal component analysis (PCA) may suffer from the sensitivity to outliers and noise. Therefore PCA based on -norm and -norm () have been s…
A general model for plane-based clustering with loss function
Zhen Wang, Yuan-Hai Shao, Lan Bai +2
In this paper, we propose a general model for plane-based clustering. The general model contains many existing plane-based clustering methods, e.g., k-plane clustering (kPC), proxi…
Ramp-based Twin Support Vector Clustering
Zhen Wang, Xu Chen, Chun-Na Li +1
Traditional plane-based clustering methods measure the cost of within-cluster and between-cluster by quadratic, linear or some other unbounded functions, which may amplify the impa…
Robust Bhattacharyya bound linear discriminant analysis through adaptive algorithm
Chun-Na Li, Yuan-Hai Shao, Zhen Wang +1
In this paper, we propose a novel linear discriminant analysis criterion via the Bhattacharyya error bound estimation based on a novel L1-norm (L1BLDA) and L2-norm (L2BLDA). Both L…