Automated classification of multi-class sleep stages classification using polysomnography signals: a nine- layer 1D-convolution neural network approach.
Santosh Kumar SatapathyD. LoganathanPublished in: Multim. Tools Appl. (2023)
Keyphrases
- multi class
- automated classification
- neural network
- multiclass classification
- support vector machine
- multi class classification
- multi class classifier
- multi class boosting
- binary classifiers
- cost sensitive
- class probabilities
- multiclass problems
- binary classification
- multiple classes
- binary and multi class
- sleep stage
- error correcting output codes
- feature selection
- eeg signals
- object detection
- multi class classifiers
- multi class problems
- multi class svm
- base classifiers
- svm classifier
- text classification
- classification accuracy
- pairwise
- signal processing
- binary classification problems
- artificial neural networks
- machine learning
- multi class object detection
- class imbalance
- multi task
- model selection
- feature vectors
- support vector
- image processing
- data mining