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Suppose I want to do k-fold cross-validation across a set of data points. Each of these data points is a member of exactly one of n classes. (For example, suppose each of the data points is a person and the class they belong to is their age in years.) I want the distribution across classes of each of my k test sets to (as closely as possible) 'match' the distribution of classes across all the data points. (And I want each data point to be in exactly one of the k test sets.) The number of points in each of the n classes need not be a multiple of k.

Is there some well-known algorithm, or, better yet, Python library for doing this?

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I believe you are looking for Stratified K-Fold Cross Validation, which preserves the distribution of classes across folds of the data.

Scikit-learn has a StratifiedKFold function for Python users!

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