
Explanation:

Use the Split data into partitions option when you want to divide the dataset into subsets of the data. This option is also useful when you want to create a custom number of folds for cross-validation, or to split rows into several groups.
* Add the Partition and Sample module to your experiment in Studio (classic), and connect the dataset.
* For Partition or sample mode, select Assign to Folds.
* Use replacement in the partitioning: Select this option if you want the sampled row to be put back into the pool of rows for potential reuse. As a result, the same row might be assigned to several folds.
* If you do not use replacement (the default option), the sampled row is not put back into the pool of rows for potential reuse. As a result, each row can be assigned to only one fold.
* Randomized split: Select this option if you want rows to be randomly assigned to folds.
If you do not select this option, rows are assigned to folds using the round-robin method.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample