Diagnosing Ensemble Few-Shot Classifiers.
Weikai YangXi YeXingxing ZhangLanxi XiaoJiazhi XiaZhongyuan WangJun ZhuHanspeter PfisterShixia LiuPublished in: IEEE Trans. Vis. Comput. Graph. (2022)
Keyphrases
- ensemble learning
- ensemble classifier
- classifier ensemble
- multiple classifiers
- ensemble pruning
- majority voting
- training data
- final classification
- individual classifiers
- feature selection
- training set
- ensemble methods
- majority vote
- accurate classifiers
- multiple classifier systems
- decision tree classifiers
- combining classifiers
- randomized trees
- class label noise
- rule induction algorithm
- base classifiers
- mining concept drifting data streams
- one class support vector machines
- classifier combination
- naive bayes
- random forests
- concept drifting data streams
- bias variance decomposition
- video sequences
- diversity measures
- ensemble classification
- ensemble members
- support vector
- weighted voting
- classifier fusion
- imbalanced data
- linear classifiers
- neural network
- random forest
- model based diagnosis
- video data
- learning algorithm
- weak classifiers
- decision trees
- text categorization
- feature set
- weak learners
- key frames
- classification models
- binary classification problems
- classification accuracy
- class labels
- prediction accuracy