The goal of this function should be to estimate the functionality of a classifier in a selected environment. This functionality usually takes as enter an m x (n+1) array of info, an integer p, the classifier it is checking, and any remaining parameters the classifier calls for will be saved in args . Here’s how it really works: It's going to very first randomly mix-up the rows of knowledge. Then it'll partition data into p equivalent parts. If p equivalent pieces are not possible then as near equal as is achievable (no mobile must have more than one much more observation than one other cells).
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