Introduction to Classification: Likelihoods, Margins, Features, and Kernels.
Dan KleinPublished in: HLT-NAACL (Tutorial Abstracts) (2007)
Keyphrases
- feature space
- feature vectors
- classification accuracy
- feature set
- classification process
- feature extraction
- svm classification
- classification models
- classification method
- svm classifier
- support vector
- training set
- extracting features
- tree kernels
- feature representation
- class labels
- multiple kernel learning
- decision trees
- benchmark datasets
- feature values
- extracted features
- gender classification
- discriminative features
- kernel learning
- feature analysis
- features extraction
- support vector machine svm
- machine learning
- pattern recognition
- high dimensionality
- classification algorithm
- kernel function
- text classification
- supervised learning
- kernel principal component analysis
- training data
- feature selection
- linear svm
- mercer kernel
- histogram intersection kernel
- discriminative information
- kernel machines
- generalization ability
- gabor filters
- kernel methods
- image features
- active learning