### Feature Importance
Feature importance is a measure of the contribution of each feature in a dataset to the model's predictions. It's a crucial aspect of feature engineering in machine learning.
**Example:** Suppose we have a dataset of house prices with features like number of bedrooms, square footage, and location. We want to determine which feature has the most impact on the house price.
**Constraints:** Use a random forest regressor to calculate feature importance.
Test Cases
Test Case 1
Input:
[[1, 2, 3], [4, 5, 6]]Expected:
[0.2, 0.3, 0.5]Test Case 2
Input:
[[7, 8, 9], [10, 11, 12]]Expected:
[0.1, 0.2, 0.7]+ 3 hidden test cases