30. A Smaller Training Set

Question:

One way to speed up an algorithm is to train it on a smaller training dataset. The tradeoff is that the accuracy almost always goes down when you do this. Let’s explore this more concretely: add in the following two lines immediately before training your classifier.



features_train = features_train[:len(features_train)/100]


labels_train = labels_train[:len(labels_train)/100]



These lines effectively slice the training dataset down to 1% of its original size, tossing out 99% of the training data. You can leave all other code unchanged. What’s the accuracy now?