random forest feature importance scikit learn code example

Example 1: random forrest plotting feature importance function

def plot_feature_importances(model):
    n_features = data_train.shape[1]
    plt.figure(figsize=(20,20))
    plt.barh(range(n_features), model.feature_importances_, align='center') 
    plt.yticks(np.arange(n_features), data_train.columns.values) 
    plt.xlabel('Feature importance')
    plt.ylabel('Feature')

Example 2: sklearn random forest feature importance

from sklearn.ensemble import RandomForestClassifier

feature_names = [f'feature {i}' for i in range(X.shape[1])]
forest = RandomForestClassifier(random_state=0)
forest.fit(X_train, y_train)

Example 3: sklearn random forest feature importance

print(__doc__)
import matplotlib.pyplot as plt