Stratified K Fold cross validation - wwbin2008/Handson_ml_demo-and-some-notes GitHub Wiki

Stratification is the process of rearranging the data to ensure each fold is a good representative of the whole. For example in a binary classification problem where each class comprises 50% of the data, it is best to arrange the data such that in every fold, each class comprises around half the instances.

Stratification is generally a better scheme, both in terms of bias and variance, when compared to regular cross-validation.