Information-Theoretic Feature Selection for Classification.
Alok A. JoshiScott M. JamesPeter H. MecklGalen B. KingKristofer JenningsPublished in: ACC (2007)
Keyphrases
- information theoretic
- feature selection
- mutual information
- information theory
- classification accuracy
- jensen shannon divergence
- theoretic framework
- feature extraction
- text classification
- information theoretic measures
- support vector
- machine learning
- feature set
- log likelihood
- relative entropy
- support vector machine
- entropy measure
- kullback leibler divergence
- image classification
- multi modality
- pattern recognition
- feature selection algorithms
- text categorization
- similarity measure
- model selection
- information bottleneck
- image registration
- feature space
- decision trees
- minimum description length
- kl divergence
- distributional clustering
- density estimation
- feature subset
- svm classifier
- naive bayes
- k nearest neighbor
- dimensionality reduction
- principal component analysis
- feature vectors
- training data