Principal minimax support vector machine for sufficient dimension reduction with contaminated data.
Jingke ZhouLixing ZhuPublished in: Comput. Stat. Data Anal. (2016)
Keyphrases
- dimension reduction
- training data
- data sets
- data analysis
- high dimensional data
- noisy data
- data sources
- support vector machine
- databases
- image data
- knowledge discovery
- input data
- low dimensional
- unsupervised learning
- data points
- original data
- feature space
- feature selection
- high dimensional problems
- sparse metric learning