Plot Feature Importance
def plot_feature_importance(importance,names,model_type):
#Create arrays from feature importance and feature names
feature_importance = np.array(importance)
feature_names = np.array(names)
#Create a DataFrame using a Dictionary
data={'feature_names':feature_names,'feature_importance':feature_importance}
fi_df = pd.DataFrame(data)
#Sort the DataFrame in order decreasing feature importance
fi_df.sort_values(by=['feature_importance'], ascending=False,inplace=True)
#Define size of bar plot
plt.figure(figsize=(10,8))
#Plot Searborn bar chart
sns.barplot(x=fi_df['feature_importance'], y=fi_df['feature_names'])
#Add chart labels
plt.title(model_type + ' FEATURE IMPORTANCE')
plt.xlabel('FEATURE IMPORTANCE')
plt.ylabel('FEATURE NAMES')
Call this by passing model.featureimportances, columns in dataset and Name of Model