def plotFeatureImportance(classifier):
featureNames = dataReader.deserializeObject("data\\misc\\columns.csv")
feature_importance = classifier.feature_importances_
# make importances relative to max importance
feature_importance = 100.0 * (feature_importance / feature_importance.max())
sorted_idx = np.argsort(feature_importance)
pos = np.arange(sorted_idx.shape[0]) + .5
plt.subplot(1, 2, 2)
plt.barh(pos, feature_importance[sorted_idx], align='center')
plt.yticks(pos,featureNames[sorted_idx])
plt.xlabel('Relative Importance')
plt.title('Variable Importance')
plt.show()
