A novel information theoretic-interact algorithm (IT-IN) for feature selection using three machine learning algorithms.
Deisy ChelliahS. BaskarN. RamarajJ. Saravanan KooriP. JeevanandamPublished in: Expert Syst. Appl. (2010)
Keyphrases
- machine learning algorithms
- information theoretic
- learning algorithm
- benchmark data sets
- mutual information
- feature selection
- machine learning
- entropy measure
- machine learning systems
- relative entropy
- log likelihood
- jensen shannon divergence
- information theory
- k means
- information theoretic measures
- minimum description length
- theoretic framework
- decision trees
- information entropy
- learning problems
- learning tasks
- image registration
- image analysis
- jensen shannon