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Hands-On Predictive Analytics with Python
book

Hands-On Predictive Analytics with Python

by Alvaro Fuentes
December 2018
Beginner to intermediate content levelBeginner to intermediate
330 pages
8h 32m
English
Packt Publishing
Content preview from Hands-On Predictive Analytics with Python

The k-fold cross-validation

So far, we have been evaluating our models in the test set. By now, it is clear why we do it; however, there is one point we have not discussed yet. Let's go back to the diamond prices problem. In this chapter, we have built a simple multiple linear regression model and we have calculated some metrics on the test set. Let's say that we will use the MAE for evaluating the model. When we calculated this metric, we got 733.67. Now let's repeat the same steps for model building:

  • Train-test split
  • Standardize the numeric features
  • Model training
  • Get predictions
  • Evaluate the model using the same metric

Here we have the code again:

## Train-test splitX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, ...
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Publisher Resources

ISBN: 9781789138719Supplemental Content