Stochastic discrimination is a general methodology for constructing classifiers appropriate for pattern recognition. It is based on combining arbitrary numbers of very weak components, which are usually generated by some pseudorandom process, and it has the property that the very complex and accurate classifiers produced in this way retain the ability, characteristic of their weak component pieces, to generalize to new data as complexity increases. These utilities provide an implementation of this algorithm.
|Tags||Scientific/Engineering Artificial Intelligence|
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