Supervised Principal Component Analysis Using a Smooth Classifier Paradigm.
Stavros J. PerantonisSergios PetridisVassilis VirvilisPublished in: ICPR (2000)
Keyphrases
- principal component analysis
- neural classifier
- feature space
- learning algorithm
- feature selection
- supervised classifiers
- supervised classification
- supervised training
- principal components
- feature reduction
- training data
- supervised learning
- multiple classifiers
- svm classifier
- independent component analysis
- decision trees
- semi supervised
- training procedure
- classification process
- linear classifiers
- support vector machine
- discriminant analysis
- covariance matrix
- classifier systems
- bayesian classifier
- classification scheme
- dimension reduction
- machine learning
- training samples
- unsupervised learning
- low dimensional
- dimensionality reduction
- class labels
- classifier combination
- feature set
- training set
- support vector
- singular value decomposition
- lower dimensional
- pattern recognition
- computer vision
- manually labeled training data