Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression.
Sean StijvenWouter MinneboKatya VladislavlevaPublished in: GECCO (Companion) (2011)
Keyphrases
- feature importance
- random forests
- symbolic regression
- random forest
- regression problems
- genetic programming
- feature selection
- feature set
- parameter optimization
- decision trees
- gene expression programming
- fitness function
- regression forests
- ensemble methods
- software package
- ensemble classifier
- ensemble learning
- logistic regression
- evolutionary algorithm
- text categorization
- genetic algorithm
- classification accuracy
- multi label
- feature extraction
- text classification
- feature space
- support vector machine
- neural network
- genetic algorithm ga
- support vector
- artificial neural networks
- machine learning algorithms
- base classifiers
- dimensionality reduction
- similarity measure
- information retrieval