In Python's scikit-learn library, sklearn.cross_validation.StratifiedKFold is a class that provides a cross-validator for stratified k-fold cross-validation. Stratified k-fold cross-validation is a variant of k-fold cross-validation, where each fold aims to have the same distribution of class labels (or target variable) as the whole dataset. This cross-validation strategy is especially useful for datasets with imbalanced class distributions, where certain classes may have very few samples. By preserving the class distribution in each fold, StratifiedKFold can provide more accurate and reliable performance estimation for classification tasks.
Python StratifiedKFold - 17 examples found. These are the top rated real world Python examples of sklearn.cross_validation.StratifiedKFold extracted from open source projects. You can rate examples to help us improve the quality of examples.