Corpus ID: 9610402

The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification

@inproceedings{Kim2014TheBC,
  title={The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification},
  author={Been Kim and C. Rudin and J. Shah},
  booktitle={NIPS},
  year={2014}
}
We present the Bayesian Case Model (BCM), a general framework for Bayesian case-based reasoning (CBR) and prototype classification and clustering. BCM brings the intuitive power of CBR to a Bayesian generative framework. The BCM learns prototypes, the "quintessential" observations that best represent clusters in a dataset, by performing joint inference on cluster labels, prototypes and important features. Simultaneously, BCM pursues sparsity by learning subspaces, the sets of features that play… Expand
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