Neyman-Pearson classification: parametrics and sample size requirement.
Xin TongLucy XiaJiacheng WangYang FengPublished in: J. Mach. Learn. Res. (2020)
Keyphrases
- sample size
- neyman pearson
- model selection
- small sample size
- small sample
- small samples
- neural network
- random sampling
- type ii
- worst case
- cross validation
- upper bound
- support vector
- support vector machine
- classification accuracy
- decision trees
- pac learning
- text classification
- variance reduction
- statistical power
- benchmark datasets
- classification algorithm
- linear discriminant analysis
- support vector machine svm
- feature vectors