Regression models: Knowledge check

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Lesson 08 / Regression models0%

1. Watch the video2. Complete the test

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1 How does a regression model learn in the supervised learning process described in the video? It learns from inputs without any known answers. It predicts by choosing a different random function for every example. It learns a function from examples of inputs paired with known outputs.

2 In the house-size and price example, what does a residual represent? The difference between an observed value and the value predicted by the fitted line. The total number of houses used to train the model. The maximum house size that the model can accept as an input.

3 What is underfitting? A model memorizing the noise in its training data. A model being too simple to capture the underlying pattern. A model performing well on both training data and unseen data.

4 Which behavior is a warning sign of overfitting? Similar, good performance on training data and previously unseen data. A model being too simple to represent the pattern in the training data. Excellent training performance but poor performance on new data because the model has learned noise.

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