Module 4 Assessment: Probabilistic Classifiers and Calibration Check

Estimated active time: 30-45 minutes

Question 1

When is this model family worth trying for the synthetic learner-support problem?

Pass answer: names a data-shape, decision, or baseline reason, not popularity.

Question 2

What preprocessing, tuning, or validation risk matters most in this module?

Pass answer: identifies a real sensitivity from the module and explains how to control it.

Question 3

What simpler baseline must the method beat?

Pass answer: includes the dummy baseline and at least one simple or transparent baseline.

Question 4

Give one reason to delay or reject this method for the first portfolio pass.

Pass answer: gives a defensible reason such as small data, runtime, instability, explanation need, or limited gain.

Question 5

What limitation should appear in the module memo?

Pass answer: states that synthetic data, validation limits, and model inspection do not prove real-world readiness.