Visualizing features importances

In this exercise, you'll determine which features were the most predictive according to the random forests regressor rf that you trained in a previous exercise.

For this purpose, you'll draw a horizontal barplot of the feature importance as assessed by rf. Fortunately, this can be done easily thanks to plotting capabilities of pandas.

We have created a pandas.Series object called importances containing the feature names as index and their importances as values. In addition, matplotlib.pyplot is available as plt and pandas as pd.

Call the .sort_values() method on importances and assign the result to importances_sorted.
Call the .plot() method on importances_sorted and set the arguments:
- kind to 'barh'
- color to 'lightgreen'

Exercise

Visualizing features importances

Instructions