sklearn random forest continuous features 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

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)