Logistic Principle Component Analysis (L-PCA) for Feature Selection in Classification.
Jitrawadee RapeepongpanPraisan PadungweangKittichai LavangnanandaPublished in: ICNC-FSKD (2018)
Keyphrases
- principle component analysis
- dimension reduction
- feature selection
- feature extraction
- feature space
- svm classifier
- independent component analysis
- pca lda
- support vector machine
- principal component analysis
- face recognition
- classification accuracy
- lower dimensional
- support vector
- kernel pca
- principal components analysis
- dimensionality reduction
- feature set
- random projections
- high dimensionality
- principal components
- multi class
- image classification
- low dimensional
- machine learning
- covariance matrix
- high dimensional feature space
- subspace methods
- feature subset
- text classification
- feature vectors
- linear discriminant analysis
- singular value decomposition
- face databases
- decision trees
- support vector machine svm
- pattern recognition
- svm classification
- nearest neighbor classifier
- independent components
- kernel methods
- image processing