Feature selection and allocation to diverse subsets for multi-label learning problems with large datasets.
Eftim ZdravevskiPetre LameskiAndrea KulakovDejan GjorgjevikjPublished in: FedCSIS (2014)
Keyphrases
- multi label
- learning problems
- learning tasks
- text categorization
- feature selection
- multi task
- binary classification
- text classification
- semi supervised learning
- multi label classification
- multi label learning
- image annotation
- image classification
- machine learning
- multi task learning
- graph cuts
- machine learning algorithms
- supervised learning
- kernel methods
- learning algorithm
- class labels
- multi class
- unsupervised learning
- knn
- support vector
- data sets
- naive bayes
- feature extraction
- unlabeled data
- multiple kernel learning
- k nearest neighbor
- transfer learning
- reinforcement learning
- computer vision
- support vector machine
- binary classifiers
- higher order