1 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
Subject Enveloped Deep Sample Fuzzy Ensemble Learning Algorithm of Parkinson's Speech Data
Yiwen Wang, Fan Li, Xiaoheng Zhang +2
Parkinson disease (PD)'s speech recognition is an effective way for its diagnosis, which has become a hot and difficult research area in recent years. As we know, there are large c…
Envelope Imbalance Learning Algorithm based on Multilayer Fuzzy C-means Clustering and Minimum Interlayer discrepancy
Fan Li, Xiaoheng Zhang, Pin Wang +1
Imbalanced learning is important and challenging since the problem of the classification of imbalanced datasets is prevalent in machine learning and data mining fields. Sampling ap…
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…