Combining multiple class distribution modified subsamples in a single tree.
Jesús M. PérezJavier MuguerzaOlatz ArbelaitzIbai GurrutxagaJosé Ignacio MartínPublished in: Pattern Recognit. Lett. (2007)
Keyphrases
- class distribution
- combining multiple
- training data
- cost sensitive
- class imbalance
- classification trees
- training set
- test set
- test data
- training examples
- training samples
- concept drift
- imbalanced data
- highly imbalanced
- highly skewed
- data sets
- unlabeled data
- class labels
- multi class
- cluster ensemble
- machine learning methods
- input image
- semi supervised
- active learning