Feature Space Enrichment by Incorporation of Implicit Features for Effective Classification.
Abhishek SrivastavaOsmar R. ZaïaneMaria-Luiza AntoniePublished in: IDEAS (2007)
Keyphrases
- feature space
- feature vectors
- classification accuracy
- feature set
- high dimensionality
- feature selection
- feature extraction
- high dimensional
- extracted features
- training samples
- support vector machine
- feature values
- training set
- dimension reduction
- image representation
- classification method
- classification models
- dimensionality reduction
- feature reduction
- kernel methods
- kernel function
- feature subset
- classification process
- svm classification
- support vector
- discriminatory power
- feature representation
- feature analysis
- input space
- high dimensional feature space
- kernel principal component analysis
- machine learning
- benchmark datasets
- co occurrence
- mean shift
- pattern recognition
- data points
- principal component analysis
- mercer kernel
- high dimensional feature spaces
- data sets
- decision trees
- linearly separable
- features extraction
- image features
- discriminative features
- image classification
- low dimensional
- text classification
- feature selection algorithms
- hyperplane