random forest feature-importances_ code example

Example 1: sklearn random forest feature importance

import pandas as pd
forest_importances = pd.Series(importances, index=feature_names)

fig, ax = plt.subplots()
forest_importances.plot.bar(yerr=std, ax=ax)
ax.set_title("Feature importances using MDI")
ax.set_ylabel("Mean decrease in impurity")
fig.tight_layout()

Example 2: sklearn random forest feature importance

import time
import numpy as np

start_time = time.time()
importances = forest.feature_importances_
std = np.std([
    tree.feature_importances_ for tree in forest.estimators_], axis=0)
elapsed_time = time.time() - start_time

print(f"Elapsed time to compute the importances: "
      f"{elapsed_time:.3f} seconds")