Classification of Stroke Severity Using Clinically Relevant Symmetric Gait Features Based on Recursive Feature Elimination With Cross-Validation.
Joohwan SungSungmin HanHeesu ParkSoree HwangSong Joo LeeJong Woong ParkInchan YounPublished in: IEEE Access (2022)
Keyphrases
- cross validation
- model selection
- clinically relevant
- support vector
- training set
- feature selection
- support vector machine
- recursive feature elimination
- terms of classification accuracy
- decision trees
- classification accuracy
- ls svm
- pattern recognition
- human recognition
- support vector machine svm
- kernel function
- training samples
- gene expression data
- radial basis function
- pattern classification
- incremental learning
- selected features
- cancer diagnosis
- neural network