Comparing the Performances of PCA (Principle Component Analysis) and LDA (Linear Discriminant Analysis) Transformations on PAF (Paroxysmal Atrial Fibrillation) Patient Detection.
Safa SadaghiyanfamMehmet KuntalpPublished in: ICBSP (2018)
Keyphrases
- principle component analysis
- pca lda
- atrial fibrillation
- linear discriminant analysis
- dimension reduction
- principal component analysis
- face recognition
- independent component analysis
- principal components analysis
- feature extraction
- ecg signals
- heart rate variability
- svm classifier
- dimensionality reduction
- feature space
- discriminant analysis
- subspace methods
- heart rate
- lower dimensional
- kernel pca
- left atrium
- singular value decomposition
- support vector
- principal components
- object detection
- detection method
- independent components
- random projections
- covariance matrix
- support vector machine svm
- low dimensional
- dimensionality reduction methods
- face databases
- high dimensional
- high dimensional data
- scatter matrix
- eeg signals
- small sample size
- feature reduction
- data sets