1. Context
Today, systems designed to check whether a banknote is true or false, to recognize a person from the sound of his or her voice or to detect outliers in a database incorporate algorithms derived from statistical learning theory, and in particular a kernel machine as a decision tool. The programming of these systems uses a set of observation-label pairs to elaborate a decision rule. This is known as statistical learning or programming by example.
The base of examples used is a sample of n realizations (xi, yi), where xi represent shapes and yi labels. The decision rule to be learned is a function from the set of observations to...
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Context
Kernels and pattern recognition
References
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