A Variable Selection Method Considering Cluster Loading for Labeled High Dimension Low Sample Size Data.
Jiaxin ChenMika Sato-IlicPublished in: KES (2015)
Keyphrases
- high dimension
- sample size
- variable selection
- small sample
- data sets
- pairwise
- data points
- model selection
- cross validation
- high dimensional
- high dimensional data
- input data
- input variables
- statistical power
- input space
- training data
- probabilistic model
- data analysis
- ls svm
- objective function
- classification accuracy
- feature space
- feature set
- unsupervised learning
- upper bound
- dimension reduction
- real valued
- feature subset
- computational complexity
- linear models
- learning algorithm