An efficient optimization approach for best subset selection in linear regression, with application to model selection and fitting in autoregressive time-series.
Leonardo Di GangiMatteo LapucciFabio SchoenAlessio SortinoPublished in: Comput. Optim. Appl. (2019)
Keyphrases
- model selection
- autoregressive
- linear regression
- subset selection
- least squares
- multivariate regression
- parameter estimation
- cross validation
- moving average
- non stationary
- random fields
- regression model
- hyperparameters
- feature selection
- gaussian markov random field
- mixture model
- sar images
- ridge regression
- variable selection
- gaussian process
- model selection criteria
- feature extraction
- machine learning
- linear regression model
- data mining
- optical flow
- learning machines
- genetic algorithm
- generalization error
- image sequences
- higher order
- feature space