3 citations · 9 across the 12 of their papers we have counts for
5 papers · 1 filter
Overlapping oriented imbalanced ensemble learning method based on projective clustering and stagewise hybrid sampling
Fan Li, Bo Wang, Pin Wang +1
The challenge of imbalanced learning lies not only in class imbalance problem, but also in the class overlapping problem which is complex. However, most of the existing algorithms…
A new Stack Autoencoder: Neighbouring Sample Envelope Embedded Stack Autoencoder Ensemble Model
Chuanyan Zhou, Jie Ma, Fan Li +3
Stack autoencoder (SAE), as a representative deep network, has unique and excellent performance in feature learning, and has received extensive attention from researchers. However,…
Envelope imbalanced ensemble model with deep sample learning and local-global structure consistency
Fan Li, Xiaoheng Zhang, Yongming Li +1
The class imbalance problem is important and challenging. Ensemble approaches are widely used to tackle this problem because of their effectiveness. However, existing ensemble meth…
Hybrid Embedded Deep Stacked Sparse Autoencoder with w_LPPD SVM Ensemble
Yongming Li, Yan Lei, Pin Wang +1
Deep learning is a kind of feature learning method with strong nonliear feature transformation and becomes more and more important in many fields of artificial intelligence. Deep a…
Classification Algorithm of Speech Data of Parkinsons Disease Based on Convolution Sparse Kernel Transfer Learning with Optimal Kernel and Parallel Sample Feature Selection
Xiaoheng Zhang, Yongming Li, Pin Wang +2
Labeled speech data from patients with Parkinsons disease (PD) are scarce, and the statistical distributions of training and test data differ significantly in the existing datasets…