Python train_test_split Guide

The train_test_split function’s purpose is:

1. Splitting the dataset into two parts, a training set and a testing set, with the option to specify the splitting ratio.
2. The dataset can be shuffled as needed.
3. Using a specified random seed can ensure consistent splitting results each time the program is run.
4. Multiple features and target variables can be simultaneously split.
5. Stratified sampling can be applied to the segmented data as needed to maintain consistency in class proportions from the original dataset.