On Aggregation in Ensembles of Multilabel Classifiers.
Vu-Linh NguyenEyke HüllermeierMichael RappEneldo Loza MencíaJohannes FürnkranzPublished in: DS (2020)
Keyphrases
- multilabel classification
- multi label
- ensemble methods
- multi label classification
- classifier training
- instance based learning
- class labels
- ensemble learning
- decision trees
- text categorization
- image classification
- graph cuts
- logistic regression
- lazy learning
- prediction accuracy
- machine learning methods
- binary classification
- base classifiers
- inter related
- naive bayes
- benchmark datasets
- base learners
- convex relaxation
- text classification
- training set
- training data
- label ranking
- random walker
- label space
- classification algorithm
- nearest neighbor
- co training
- binary classifiers
- feature selection
- unlabeled data
- similarity measure
- multi class
- markov random field
- neural network
- machine learning
- feature set
- max margin
- inductive learning
- instance selection
- svm classifier
- feature subset