Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification.
Zhen-Xin NiuLiang-Rui RenRong ZhuXiang-Zhen KongYing-Lian GaoJin-Xing LiuPublished in: ICIC (2) (2021)
Keyphrases
- extreme learning machine
- risk sensitive
- training samples
- feature space
- support vector
- feedforward neural networks
- training set
- pattern classification
- optimal control
- class labels
- support vector machine svm
- utility function
- kernel methods
- supervised learning
- support vector machine
- feature selection
- multi layer perceptron
- feed forward neural networks
- feature vectors
- feature set
- cross validation
- hidden nodes
- high dimensional
- feature extraction