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

Understand

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 important roles in the characterization of the prototypes.