You can have your ensemble and run it too - Deep Ensembles Spread Over Time.
Isak MedingAlexander BodinAdam TonderskiJoakim JohnanderChristoffer PeterssonLennart SvenssonPublished in: ICCV (Workshops) (2023)
Keyphrases
- ensemble methods
- ensemble learning
- neural network ensemble
- ensemble selection
- ensemble members
- classifier ensemble
- base classifiers
- random forests
- ensemble classifier
- weighted voting
- imbalanced data
- tree ensembles
- decision trees
- prediction accuracy
- generalization ability
- ensemble feature selection
- decision tree ensembles
- variable selection
- learning algorithm
- random forest
- base learners
- multiple classifier systems
- benchmark datasets
- neural network ensembles
- feature selection
- multi class
- generalization error
- deep learning
- competitive learning
- naive bayes
- feature ranking
- support vector machine
- classification accuracy
- parameter settings
- selection strategy
- neural network