Extreme Phenotype Sampling Improves LASSO and Random Forest Marker Selection for Complex Traits.
Cai JohnWellington MucheroScott EmrichPublished in: BIBM (2020)
Keyphrases
- random forest
- random forests
- decision trees
- imbalanced data
- feature set
- ensemble methods
- sample size
- feature importance
- ensemble classifier
- model selection
- support vector
- feature selection
- computer vision
- gene expression
- fold cross validation
- naive bayes
- multi label
- text classification
- ensemble learning
- simulated annealing
- active learning