DC programming and DCA for sparse Fisher linear discriminant analysis
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-016-2216-9
Abstract: Abstract We consider the supervised pattern classification in the high-dimensional setting, in which the number of features is much larger than the number of observations. We present a novel approach to the sparse Fisher linear… read more here.
Keywords: fisher linear; sparse fisher; programming dca; linear discriminant ... See more keywords
Automatic Detection of Epileptic Seizures in EEG Using Sparse CSP and Fisher Linear Discrimination Analysis Algorithm
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Medical Systems"
DOI: 10.1007/s10916-019-1504-1
Abstract: In order to realize the automatic epileptic seizure detection, feature extraction and classification of electroencephalogram (EEG) signals are performed on the interictal, the pre-ictal, and the ictal status of epilepsy patients. There is no effective… read more here.
Keywords: detection; detection epileptic; analysis; fisher linear ... See more keywords
Fisher's Linear Discriminant Analysis With Space-Folding Operations.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3233572
Abstract: Fisher's linear discriminant analysis (LDA) is an easy-to-use supervised dimensionality reduction method. However, LDA may be ineffective against complicated class distributions. It is well-known that deep feedforward neural networks with rectified linear units as activation… read more here.
Keywords: linear discriminant; discriminant analysis; space; fisher linear ... See more keywords