Data Clustering Method for Bayesian Data Reduction
Patent application, Filed 20 Mar 2006
DEPARTMENT OF THE NAVY WASHINGTON DC
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This invention is a method of training a mean-field Bayesian data reduction algorithm BDRA based classifier which includes using an initial training for determining the best number of levels. The Mean-Field BDRA is then retrained for each point in a target data set and training errors are calculated for each training operation. Cluster candidates are identified as those with multiple points having a common training error. Utilizing these cluster candidates and previously identified clusters as the identified target data, the clusters can be confirmed by comparing a newly calculated training error with the previously calculated common training error for the cluster. The method can be repeated until all cluster candidates are identified and tested.
- Statistics and Probability
- Target Direction, Range and Position Finding