SAMUR: Stochastic Augmentation of Matched Data Using Restriction
Methods
Augmenting a matched data set by generating multiple stochastic, matched samples from the data using a
multi-dimensional histogram constructed from dropping the input matched data into a multi-dimensional grid built on
the full data set. The resulting stochastic, matched sets will likely provide a collectively higher coverage of the full
data set compared to the single matched set. Each stochastic match is without duplication, thus allowing downstream
validation techniques such as cross-validation to be applied to each set without concern for overfitting.
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