On the Complexity of Discrete Feature Selection for Optimal Classification.
José M. PeñaRoland NilssonPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2010)
Keyphrases
- feature selection
- classification accuracy
- feature subset
- text classification
- support vector machine
- feature space
- high dimensionality
- classification performances
- feature extraction
- feature selection algorithms
- worst case
- pattern recognition
- classification models
- support vector
- machine learning
- unsupervised learning
- feature set
- method for feature selection
- naive bayes
- model selection
- discriminative features
- support vector machine svm
- image classification
- supervised learning
- accurate classification
- feature selection and classification
- bayesian classifier
- feature subset selection
- class separability
- dimension reduction
- neural network
- knn
- dynamic programming
- high dimensional
- decision trees
- microarray data
- classification method
- classification algorithm
- class labels
- text categorization
- mutual information
- feature vectors
- web page classification
- computational complexity
- data sets
- support vector classification
- binary decision tree