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16 lines
910 B
16 lines
910 B
2 years ago
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# Exercise 3: Train test split
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The goal of this exercise is to learn to split a data set. It is important to understand why we split the data in two sets. To put it in a nutshell: the Machine Learning model learns on the training data and evaluates on the data the model hasn't seen before: the testing data.
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This video gives a basic and nice explanation: https://www.youtube.com/watch?v=_vdMKioCXqQ
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This article explains the conditions to split the data and how to split it: https://machinelearningmastery.com/train-test-split-for-evaluating-machine-learning-algorithms/
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```python
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X = np.arange(1,21).reshape(10,-1)
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y = np.arange(1,11)
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```
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1. Split the data using `train_test_split` with `shuffle=False`. The test set represents 20% of the total size of the data set. Print X_train, y_train, X_test, y_test.
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https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
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