Python Machine Learning Cookbook

Extracting learning curves

Learning curves help us understand how the size of our training dataset influences the machine learning model. This is very useful when you have to deal with computational constraints. Let's go ahead and plot the learning curves by varying the size of our training dataset.

How to do it…

1. Add the following code to the same Python file, as in the previous recipe:

   # Learning curves from sklearn.learning_curve import learning_curve classifier = RandomForestClassifier(random_state=7) parameter_grid = np.array([200, 500, 800, 1100]) train_sizes, train_scores, validation_scores = learning_curve(classifier, X, y, train_sizes=parameter_grid, cv=5) print "\n##### LEARNING CURVES #####" print "\nTraining scores:\n", train_scores print ...