High-dimensional variable selection in regression and classification with missing data.
Qi GaoThomas C. M. LeePublished in: Signal Process. (2017)
Keyphrases
- variable selection
- missing data
- high dimensional
- model selection
- cross validation
- linear models
- dimension reduction
- multiple imputation
- regression problems
- feature selection
- high dimensionality
- input variables
- logistic regression models
- incomplete data
- support vector
- missing values
- pattern recognition
- feature space
- high dimensional data
- regression model
- low dimensional
- low rank
- matrix factorization
- training set
- decision trees
- support vector machine svm
- machine learning
- naive bayes classifier
- class labels
- machine learning algorithms
- text classification
- k nearest neighbour
- imputation methods
- preprocessing
- database
- feature extraction
- dimensionality reduction
- nearest neighbor