Subspace based least squares support vector machines for pattern classification.
Takuya KitamuraShigeo AbeKazuhiro FukuiPublished in: IJCNN (2009)
Keyphrases
- pattern classification
- least squares support vector machine
- ls svm
- feature extraction
- pattern recognition
- least squares
- low dimensional
- principal component analysis
- high dimensional data
- dimensionality reduction
- improved algorithm
- principal components
- high dimensional
- data sets
- variable selection
- statistical learning theory
- feature space
- input variables
- input data
- bayesian framework
- model selection
- image classification
- machine learning