A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities

Key Points

• This research aims to develop a Bayesian dual clustering approach to enhance the understanding of data and parameter granularities.
• Developed a Bayesian dual clustering framework.
• Applied the method to infer data and parameter granularities.
• Used statistical analysis to validate the approach.
• The method successfully inferred granularities for various datasets.
• Demonstrated improvements in clustering accuracy over traditional methods.