April 2015
Beginner
258 pages
5h 48m
English
If you have run the previous experiment, you may have realized that:
Unfortunately, relying on the validation and testing phases of samples brings uncertainty along with a strong reduction of the learning examples for training (the fewer the examples, the more the variance of the obtained model).
A solution is to use cross-validation, and Scikit-learn offers a complete module for cross-validation and performance evaluation (sklearn.cross_validation).
By resorting to cross-validation, you'll just need to separate your data into a training and test set, and you will be able to use the training ...