A Correlation-Redundancy Guided Evolutionary Algorithm and Its Application to High-Dimensional Feature Selection in Classification.
Xiang SunShunsheng GuoShiqiao LiuJun GuoBaigang DuPublished in: Neural Process. Lett. (2024)
Keyphrases
- feature selection
- high dimensional
- high dimensionality
- classification accuracy
- feature space
- classification models
- support vector
- feature set
- text classification
- feature extraction
- machine learning
- dimension reduction
- discriminative features
- small sample
- feature subset
- support vector machine
- dimensionality reduction
- text categorization
- feature selection algorithms
- feature vectors
- image classification
- pattern recognition
- correlation coefficient
- feature subset selection
- microarray data
- classification algorithm
- bayes classifier
- high dimensional data
- genetic algorithm
- high dimension
- classification method
- training samples
- knn
- support vector machine svm
- feature reduction
- informative features
- fold cross validation
- training set
- feature selection and classification
- model selection
- unsupervised learning
- method for feature selection
- microarray datasets
- class separability
- small sample size
- feature weighting
- classification performances
- support vector classification
- wrapper feature selection
- active learning
- classification rate
- class imbalance
- variable selection
- information gain
- multi class
- mutual information
- low dimensional
- data sets
- cross validation
- naive bayes