High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking.
Fan WangSach MukherjeeSylvia RichardsonSteven M. HillPublished in: Stat. Comput. (2020)
Keyphrases
- variable selection
- finite sample
- high dimensional
- model selection
- sample size
- nearest neighbor
- cross validation
- statistical learning theory
- uniform convergence
- input variables
- regression model
- generalization error
- generalization bounds
- statistical learning
- dimension reduction
- prediction model
- error bounds
- high dimensional data
- low dimensional
- ranking algorithm
- reproducing kernel hilbert space
- high dimensionality
- dimensionality reduction
- ranking functions
- support vector
- machine learning
- neural network
- support vector machine
- ls svm
- kernel function
- vc dimension
- unsupervised learning
- hyperparameters
- data points
- gaussian processes
- pattern recognition
- feature selection
- learning algorithm