A parsimonious SVM model selection criterion for classification of real-world data sets via an adaptive population-based algorithm.
Omid Naghash-AlmasiMohammad Hassan KhoobanPublished in: Neural Comput. Appl. (2018)
Keyphrases
- support vector machine svm
- classification algorithm
- real world data sets
- classification method
- support vector
- multi class classification
- particle swarm optimization
- data sets
- optimization algorithm
- preprocessing
- computational complexity
- detection algorithm
- image classification
- simulated annealing
- support vector machine
- classification rate
- classification scheme
- combinatorial optimization
- probabilistic model
- pattern recognition
- objective function
- feature selection
- feature vectors
- svm classifier
- differential evolution
- svm classification
- decision function
- empirical studies
- feature set
- multi class
- classification accuracy
- k means
- training set
- optimal solution
- learning algorithm
- machine learning