Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers.
Apoorv VyasNataraj JammalamadakaXia ZhuDipankar DasBharat KaulTheodore L. WillkePublished in: ECCV (8) (2018)
Keyphrases
- ensemble learning
- training set
- training data
- multiple classifiers
- ensemble pruning
- ensemble classifier
- majority voting
- feature selection
- classifier ensemble
- detection algorithm
- weighted voting
- decision trees
- final classification
- neural network
- ensemble methods
- detection method
- decision tree classifiers
- detection rate
- accurate classifiers
- multiple classifier systems
- naive bayes
- ensemble classification
- weak classifiers
- object detection
- support vector
- feature ranking
- binary classification problems
- combining classifiers
- ensemble members
- class label noise
- random forest
- base classifiers
- false positives
- logistic regression
- individual classifiers
- discriminative classifiers
- classification models
- data distribution
- test set
- machine learning algorithms
- supervised learning
- probability distribution
- randomized trees
- boosted classifiers
- mining concept drifting data streams
- machine learning