Top 7 cross validation techniques with Python Code - Analytics Vidhya

Not suitable for Time Series data: For Time Series data the order of the samples matter. But in Stratified Cross-Validation, samples are selected in random order. LeavePOut cross-validation is an exhaustive cross-validation technique, in which p-samples are used as the validation set and remaining n-p samples are used as the training set. Suppose we have 100 samples in the dataset. If we use p 10 then in each iteration 10 values will be used as a validation set and the remaining 90 samples as the training set. This process is repeated till the whole dataset gets divided on the validation set of p-samples and n-p training samples. All the data samples get used as both training and validation samples.