Feature Selection for Regression Problems Based on the Morisita Estimator of Intrinsic Dimension: Concept and Case Studies.
Jean GolayMichael LeuenbergerMikhail F. KanevskiPublished in: CoRR (2016)
Keyphrases
- regression problems
- feature selection
- intrinsic dimension
- linear regression
- genetic programming
- high dimensional data
- cross validation
- multi task
- least squares
- input space
- dimension reduction
- support vector machine
- hyperparameters
- maximum likelihood
- high dimensions
- model selection
- support vector
- learning machines
- feature extraction
- random forests
- text categorization
- low dimensional
- dimensionality reduction
- multi class
- machine learning
- kernel function
- neural network
- random sampling
- image classification
- pattern recognition