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SYSTEM AND METHOD FOR PERFORMING K-NEAREST NEIGHBOR SEARCH BASED ON MINIMAX DISTANCE MEASURE AND EFFICIENT OUTLIER DETECTION
SYSTEM AND METHOD FOR PERFORMING K-NEAREST NEIGHBOR SEARCH BASED ON MINIMAX DISTANCE MEASURE AND EFFICIENT OUTLIER DETECTION
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机译:基于minimax距离测量和有效离群点检测的k近邻搜索系统和方法
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摘要
A system and method enable a set of dataset objects that are K-nearest neighbors (K-NN), based on their Minimax distances to a test object, to be identified without computing the all-pair Minimax distances directly. A pairwise distance between the test object and each dataset object is computed. Iteratively, one of the dataset objects is selected to add to a K-NN set until the K-NN set includes a predefined number of nearest neighbors. The selected dataset object at each iteration is the one for which there is no other unselected dataset object which has a smaller pairwise distance to any of a current subset of objects than the selected dataset object. The current subset of objects includes the test object and the dataset objects currently in the K-NN set. After the K-NN set is identified it may be output or used to generate other information, such as a test object label.
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