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#fisher_kernel

Fisher kernel

In statistical classification, the Fisher kernel, named after Ronald Fisher, is a function that measures the similarity of two objects on the basis of sets of measurements for each object and a statistical model. In a classification procedure, the class for a new object can be estimated by minimising, across classes, an average of the Fisher kernel distance from the new object to each known member of the given class.

Wed 24th

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