The Strongest Columns, One by One

10 pts · 10 coins

Machine Learning in CodeEasy

The Strongest Columns, One by One

A clinic wants a shorter test. You score each of the thirty columns on its own against the diagnosis and keep the strongest few.

Task: write kbest_columns(k).

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 SelectKBest(f_classif, k=k) on the training rows.

Return the names of the kept columns as a list, in the order they appear in the data.

Examples

k = 5

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

k = 2

returns ['mean concave points', 'worst concave points']

Hints

solution.py

1from sklearn.datasets import load_breast_cancer
2from sklearn.feature_selection import SelectKBest, f_classif
3from sklearn.model_selection import train_test_split
4
5
6def kbest_columns(k):
7    pass
8