With about 20 training examples, which decision is likely to have the larger effect?

Traditional algorithms always outperform neural networks on small datasets.

With about 20 examples, _____ can matter more than algorithm choice.

Match each small-data claim with its meaning.

Order the reasoning for choosing what to prioritize with very little training data.

Explain why algorithm choice may be secondary in a very small data regime.

Diagnose the priority for a team training models on only 20 examples.

Why can a traditional algorithm's small-data advantage be uncertain?

Which conclusion best reflects the source's comparison across dataset sizes?

With 20 examples, feature design may deserve more attention than switching model families.