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US08346684B2 Pattern classification method 有权
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Pattern classification method
Abstract:
For assigning a test pattern to a class chosen from a predefined set of classes, the class membership probability for the test pattern is calculated as well as the confidence interval for the class membership probability based upon a number of training patterns in a neighborhood of the test pattern in the feature space. The number of training patterns in the neighborhood of the test pattern is obtained from computing a convolution of a density function of the training patterns with a Gaussian smoothing function centered on the test pattern, where the density function of the training patterns is represented as a mixture of Gaussian functions. The convolution of the smoothing function and the mixture of Gaussian functions can be expressed analytically.
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