Application of Machine Learning to Sleep Stage Classification.
Andrew SmithHardik AnandSnezana MilosavljevicKatherine M. RentschlerAna PocivavsekHomayoun ValafarPublished in: CSCI (2021)
Keyphrases
- sleep stage
- machine learning
- pattern recognition
- classification accuracy
- feature vectors
- support vector machine svm
- sleep apnea
- automated classification
- text classification
- image classification
- support vector machine
- feature space
- feature extraction
- decision trees
- real time
- training set
- computer vision
- automatic classification
- pattern classification
- classification algorithm
- cross validation
- database
- svm classifier
- decision rules
- class labels
- benchmark data sets
- incremental learning
- cost sensitive
- unsupervised learning
- supervised classification
- classification systems
- accuracy rate
- correct classification
- model selection
- social networks
- preprocessing