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The problem of selecting a subset of relevant features is classic and found in many branches of science including—examples in pattern recognition. In this paper, we propose a new feature selection criterion based on low-loss nearest neighbor classification and a novel feature selection algorithm that optimizes the margin of nearest neighbor classification through minimizing its loss function. At the...
The image Euclidean distance (IMED) considers the spatial relationship between the pixels of different images and can easily be embedded in existing image recognition algorithms that are based on Euclidean distance. IMED uses the prior knowledge that pixels located near one another have little variance in gray scale values, and defines a metric matrix according to the spatial distance between pixels...
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