Finding the Number of Clusters in a Dataset Using an Information Theoretic Hierarchical Algorithm.
Mehdi AghagolzadehHamid Soltanian-ZadehBabak Nadjar AraabiAli AghagolzadehPublished in: ICECS (2006)
Keyphrases
- information theoretic
- k means
- mutual information
- cluster centers
- relative entropy
- synthetic datasets
- learning algorithm
- entropy measure
- log likelihood
- information theory
- information bottleneck
- hierarchical clustering
- expectation maximization
- probabilistic model
- em algorithm
- kl divergence
- multi modality
- theoretic framework
- minimum description length
- bregman divergences
- image analysis
- similarity measure
- clustering algorithm