Generating fuzzy rule base classifier for highly imbalanced datasets using a hybrid of evolutionary algorithms and subtractive clustering.
Mahdi MahdizadehMahdi EftekhariPublished in: J. Intell. Fuzzy Syst. (2014)
Keyphrases
- fuzzy rules
- evolutionary algorithm
- subtractive clustering
- membership functions
- base classifiers
- class distribution
- rule base
- fuzzy model
- fuzzy sets
- ensemble methods
- fuzzy logic
- multi class
- test data
- fuzzy controller
- rule sets
- genetic programming
- decision trees
- random forest
- ensemble learning
- benchmark datasets
- ensemble classifier
- data sets
- naive bayes
- simulated annealing
- fitness function
- class labels
- training set
- decision making
- imbalanced data
- training samples
- input output
- supervised learning
- expert systems
- class imbalance
- decision boundary
- genetic algorithm
- neural network