A first approach towards the usage of classifiers' performance to create fuzzy measures for ensembles of classifiers: a case study on highly imbalanced datasets.
Mikel UrizDaniel PaternainHumberto BustinceMikel GalarPublished in: FUZZ-IEEE (2018)
Keyphrases
- decision trees
- ensemble learning
- imbalanced data
- support vector
- ensemble classifier
- data sets
- naive bayes
- training data
- machine learning
- classifier ensemble
- machine learning methods
- machine learning algorithms
- svm classifier
- test data
- training examples
- classification models
- decision boundary
- pattern recognition
- highly imbalanced
- high dimensional
- feature selection
- fuzzy measures
- learning algorithm