Split data set

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• In supervised learning you receive a dataset of N elements (N rows) in each row you have X features (column) + 1 or more results y (also column)
• You can divide the rows into two parts: training and testing.
• You use the training part to train your model and you use the testing part to check how good your model can predict other values.
• train_test_split() of scikit-learn can do this.

• examples/ml/basic_linear_regression_more_data.ipynb

• fix the seed by setting random_state to any fixed non-negative integer
• stratify splitting for classification of inbalanced datasets