发明名称 |
Data clustering method for bayesian data reduction |
摘要 |
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.
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申请公布号 |
US7587374(B1) |
申请公布日期 |
2009.09.08 |
申请号 |
US20060387080 |
申请日期 |
2006.03.20 |
申请人 |
THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY |
发明人 |
LYNCH ROBERT S.;WILLETT PETER K. |
分类号 |
G06F15/18 |
主分类号 |
G06F15/18 |
代理机构 |
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地址 |
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