Improvement of Learning Algorithm for the Multi-instance Multi-label RBF Neural Networks Trained with Imbalanced Samples.
Cunhe LiGuoqiang ShiPublished in: J. Inf. Sci. Eng. (2013)
Keyphrases
- multi instance
- multi label
- rbf neural network
- learning algorithm
- radial basis function
- learning tasks
- training set
- text categorization
- multi label classification
- single instance
- training samples
- training examples
- image classification
- class labels
- graph cuts
- multi label learning
- binary classification
- image annotation
- unlabeled data
- supervised learning
- training data
- class distribution
- semi supervised learning
- bp neural network
- class imbalance
- neural network model
- minority class
- real valued
- back propagation
- data sets
- machine learning
- active learning
- neural network
- cost sensitive
- text classification
- learning problems
- support vector
- machine learning algorithms
- imbalanced datasets
- generalization error
- reinforcement learning
- base learners
- sampling methods
- artificial neural networks
- image segmentation
- feature extraction
- markov random field
- labeled data
- transfer learning