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A SYSTEM AND METHOD FOR A SPARSE KERNEL EXPANSION FOR A BAYES CLASSIFIER
A SYSTEM AND METHOD FOR A SPARSE KERNEL EXPANSION FOR A BAYES CLASSIFIER
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机译:贝叶斯分类器的稀疏核扩展的系统和方法
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摘要
A method and device having instructions for analyzing input data-space by learning classifiers include choosing a candidate subset from a predetermined training data-set that is used to analyze the input data-space. Candidates are temporarily added from the candidate subset to an expansion set to generate a new kernel space for the input data-space by predetermined repeated evaluations of leave-one-out errors for the candidates added to the expansion set. This is followed by removing the candidates temporarily added to the expansion set after the leave-one-out error evaluations are performed, and selecting the candidates to be permanently added to the expansion set based on the leave-one-out errors of the candidates temporarily added to the expansion set to determine the one or more classifiers
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