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Module 6 · Concurrency, OS, ML Interview Topics
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ML: train/val/test split discipline
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📝 **Question:** Why a separate validation set? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
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📝 **Question:** Why a separate validation set? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
A
More splits give you more data — three splits triples your effective dataset size and stabilises the metrics.
B
Validation tunes hyperparameters; test gives honest final score never touched during dev.
C
Same as the test set — sklearn's `train_test_split` is the canonical pattern and validation is just naming.
D
Doesn't really matter — k-fold cross-validation on the train set already gives an unbiased estimate of generalisation.
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