Answers for "cross validation methods"

cross validation

Cross-validation is a resampling procedure used to evaluate machine learning models on a limited data sample. The procedure has a single parameter called k that refers to the number of groups that a given data sample is to be split into. As such, the procedure is often called k-fold cross-validation.

cross validation error

cross validation error

cross validation error

ModuleNotFoundError: No module named 'sklearn.cross_validation'