Comparison of t-test ranking with PCA and SEPCOR feature selection for wake and stage 1 sleep pattern recognition in multichannel electroencephalograms.
T. K. Padma ShriNatarajan SriraamPublished in: Biomed. Signal Process. Control. (2017)
Keyphrases
- pattern recognition
- feature selection
- feature extraction
- dimensionality reduction
- principal component analysis
- machine learning
- ranking algorithm
- principal components
- feature space
- sparse pca
- signal processing
- text categorization
- support vector machine svm
- face recognition
- image processing
- neural network
- principle component analysis
- feature reduction
- dimension reduction
- ranking functions
- high dimensional data
- learning to rank
- mutual information
- image analysis
- computer vision
- web search
- linear discriminant analysis
- high dimensionality
- multi class
- high dimensional
- support vector
- pattern classification
- information retrieval
- feature ranking
- negative matrix factorization
- sleep stage
- linear discriminate analysis
- data sets
- principal components analysis
- ranked list
- microarray data
- independent component analysis
- model selection
- fuzzy sets
- classification accuracy