Pass or Fail?

10 pts · 10 coins

Machine Learning in CodeEasy

Pass or Fail?

A tutor recorded how many hours each student studied (hours) and whether they passed (passed: 1 for pass, 0 for fail).

Write predict_pass(hours, passed, new_hours).

Build make_pipeline(StandardScaler(), LogisticRegression(max_iter=1000)).
Fit it with hours as the only feature.
Predict pass (1) or fail (0) for every value in new_hours, in order.

Return the predictions as a list of ints.

Examples

hours = [0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5]

passed = [0, 0, 0, 0, 1, 0, 1, 1, 1, 1]

new_hours = [0.8, 4.8]

returns [0, 1]

hours = [0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5]

passed = [0, 0, 0, 0, 1, 0, 1, 1, 1, 1]

new_hours = [3.3, 1.2]

returns [1, 0]

Hints

solution.py

1import numpy as np
2from sklearn.linear_model import LogisticRegression
3from sklearn.pipeline import make_pipeline
4from sklearn.preprocessing import StandardScaler
5
6
7def predict_pass(hours, passed, new_hours):
8    pass
9