Click4Ai

485.

Medium

### Feature Selection

In this problem, you will learn how to select the most relevant features for a machine learning model. Feature selection is an important step in the machine learning pipeline, as it can improve the model's performance and reduce overfitting.

**Example:** Select the top 3 features for the Boston housing dataset using mutual information.

**Constraints:** Use the NumPy and SciPy libraries for this problem.

Your task is to implement a function that selects the top 3 features for the Boston housing dataset using mutual information.

Test Cases

Test Case 1
Input: [[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]]
Expected: [0, 1, 2]
Test Case 2
Input: [[20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39]]
Expected: [0, 1, 2]
+ 3 hidden test cases