Graded Quiz: Model Refinement >> Data Analysis with Python
TOTAL POINTS 5
1.What is the output of the following code?
cross_val_predict (lr2e, x_data, y_data, cv=3)
1 point
The average R^2 on the test data for each of the two folds
This function finds the free parameter alpha
2.What dictionary value would we use to perform a grid search to determine if normalization should be used and for testing the following values of alpha? 1,10, 100
1 point
alpha=[1,10,100]
normalize=[True,False]
[{‘alpha’:[1,10,100],‘normalize’:[True,False]} ]
{‘alpha’: [1,10,100]}]
3. You have a linear model; the average R^2 value on your training data is 0.5, you perform a 100th order polynomial transform on your data then use these values to train another model. After this step, your average R^2 is 0.99; which of the following comments is correct?
1 point
100-th order polynomial will work better on unseen data
You should always use the simplest model
The results on your training data is not the best indicator of how your model performs; you should use your test data to get a better idea
4.Consider the following diagram of 4 fold cross-validation. From the diagram how many folds are used for training?
1 point
4
1
3
5.The following is an example of what?
1 point
Overfitting
Perfect fit
Underfitting
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