Deep Learning · Module 4
Answers and explanations · Decide what the model is allowed to learn from
Compare these references after your own attempt. You can read them at any time; they do not record a live model or vendor run.
Deep Learning · Module 4
Compare these references after your own attempt. You can read them at any time; they do not record a live model or vendor run.
04A. Check counts 60/20/20, pairwise-empty intersections and union equal to all 100 original IDs. Deliberately inserting a training ID into validation must fail. Counts alone cannot detect overlap.
04B. Training mean=4; population variance=(4+0+4)/3=8/3; standard deviation≈1.632993. Transforming 20 gives (20-4)/1.632993≈9.797959. Using all four values gives mean 8, standard deviation sqrt50≈7.071068 and transformed value≈1.697056. The validation value has changed the fitted transform; withholding its label does not remove this leakage.
04C. Without dropping: 8,8,8,8,3. With dropping: 8,8,8,8 and three unmeasured rows. Evaluation should retain all relevant observations. Weight batch losses by their sample counts.