Using cellular evolution for diversification of the balance between accurate and interpretable fuzzy knowledge bases for classification.
Adam GhandarZbigniew MichalewiczPublished in: IEEE Congress on Evolutionary Computation (2011)
Keyphrases
- knowledge base
- pattern recognition
- fuzzy classification
- machine learning
- classification method
- supervised learning
- fuzzy sets
- support vector machine
- knowledge acquisition
- classification algorithm
- classification rules
- classification scheme
- accurate classification
- decision trees
- fuzzy classifier
- model selection
- neural network
- data sets
- classification accuracy
- fuzzy logic
- support vector
- fuzzy rule based classifier
- feature extraction
- rule extraction
- classification systems
- high quality
- automatic classification
- expert systems
- high accuracy
- cellular automata
- class labels
- support vector machine svm
- knowledge representation
- training samples
- accurate classifiers
- multi class
- learning algorithm
- image classification
- rule generation
- clustering analysis
- decision rules
- machine learning algorithms
- pattern classification
- knowledge sources
- training set