Minimising redundancy, maximising relevance: HRV feature selection for stress classification.
Isibor Kennedy IhianlePedro MachadoKayode OwaDavid Ada AdamaRichard I. OtukaAhmad LotfiPublished in: Expert Syst. Appl. (2024)
Keyphrases
- feature selection
- classification accuracy
- text classification
- classification models
- feature extraction
- support vector
- machine learning
- feature set
- support vector machine
- feature space
- multi class
- dimension reduction
- pattern recognition
- accurate classification
- irrelevant features
- feature ranking
- training set
- feature subset selection
- discriminative features
- feature subset
- high dimensionality
- classification method
- bayes classifier
- naive bayes
- class separability
- unsupervised learning
- classification performances
- mutual information
- preprocessing
- method for feature selection
- web page classification
- redundant features
- minimum redundancy
- small sample
- feature relevance
- support vector machine svm
- text categorization
- model selection
- dimensionality reduction
- supervised learning
- instance selection
- feature selection algorithms
- cross validation
- svm classifier
- class labels
- data pre processing
- image classification
- data sets