What the Forest Leaned On — easy Machine Learning in Code problem | Incognition

What the Forest Leaned On

10 pts · 10 coins

Machine Learning in CodeEasy

What the Forest Leaned On

A forest counts how much each column improved its splits while it trained. That count is free to read once the forest is fitted.

Task: write top_built_in(n).

Load the data with load_breast_cancer(return_X_y=True, as_frame=True).
Split it with train_test_split(X, y, test_size=0.25, random_state=0, stratify=y).
Fit RandomForestClassifier(n_estimators=100, random_state=0) on the training rows.

Return the names of the n columns with the highest feature_importances_, most important first.

Examples

n = 3

returns ['worst perimeter', 'worst radius', 'worst concave points']

n = 1

returns ['worst perimeter']

Hints

solution.py

1import pandas as pd
2from sklearn.datasets import load_breast_cancer
3from sklearn.ensemble import RandomForestClassifier
4from sklearn.model_selection import train_test_split
5
6
7def top_built_in(n):
8    pass
9