Optimizing Feature Selection for Binary Classification with Noisy Labels: A Genetic Algorithm Approach.
Vandad ImaniElaheh MoradiCarlos Sevilla-SalcedoVittorio FortinoJussi TohkaPublished in: CoRR (2024)
Keyphrases
- binary classification
- multi label
- feature selection
- genetic algorithm
- text categorization
- multi class
- support vector
- multi label classification
- support vector machine
- text classification
- multi class classification
- binary classification problems
- cost sensitive
- class imbalance
- pairwise
- learning problems
- training examples
- image classification
- neural network
- classification accuracy
- graph cuts
- generalization error
- prediction accuracy
- feature set
- genetic algorithm ga
- binary classifiers
- fitness function
- class labels
- feature extraction
- training data
- multi task
- kernel function
- simulated annealing
- k nearest neighbor
- cross validation
- optimization method
- learning tasks
- machine learning
- feature subset
- ensemble methods
- naive bayes
- training set
- semi supervised learning
- dimensionality reduction
- learning algorithm
- multiclass problems
- svm classifier
- loss function
- genetic programming
- supervised learning
- semi supervised
- evolutionary algorithm
- reinforcement learning
- data mining