Split data set

• train_test_split}

• 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