Classification of iris regions using Principal Component Analysis and Support Vector Machine.
Abdul Jalil Nor'ainiRohilah SahakAzilah SaparonPublished in: ICSIPA (2013)
Keyphrases
- support vector machine
- principal component analysis
- classification method
- support vector machine svm
- svm classifier
- support vector
- classification algorithm
- machine learning
- feature space
- feature vectors
- pattern recognition
- feature selection
- feature extraction
- classification accuracy
- dimension reduction
- decision boundary
- high classification accuracy
- kernel principal component analysis
- region of interest
- generalization ability
- training set
- image classification
- text classification
- pattern classification
- multi class
- dimension reduction methods
- soft margin
- feature reduction
- supervised learning
- decision trees
- small sample
- iris recognition
- linear discriminant analysis
- kernel methods
- covariance matrix
- kernel function
- k nearest neighbor
- dimensionality reduction
- decision forest
- sequential minimal optimization
- data sets
- multi class support vector machines
- discriminant analysis
- singular value decomposition
- training samples
- feature set
- input image
- high dimensional
- face recognition
- neural network