Semi-supervised recursively partitioned mixture models for identifying cancer subtypes.
Devin C. KoestlerCarmen J. MarsitBrock C. ChristensenMargaret R. KaragasRaphael BuenoDavid J. SugarbakerKarl T. KelseyEugene Andres HousemanPublished in: Bioinform. (2010)
Keyphrases
- mixture model
- semi supervised
- unsupervised learning
- generative model
- breast cancer
- gaussian mixture model
- cancer diagnosis
- em algorithm
- semi supervised learning
- density estimation
- expectation maximization
- probabilistic model
- model selection
- maximum likelihood
- gene expression profiles
- active learning
- unlabeled data
- finite mixtures
- supervised learning
- mixture components
- probability density function
- language model
- labeled data
- pairwise constraints
- lung cancer
- bayesian information criterion
- mixture modeling
- model based clustering
- data mining
- automatic model selection
- subspace learning
- gene selection
- pairwise
- image segmentation
- learning algorithm