Why is adding more data alone insufficient when training error exceeds the desired performance level?
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Why is adding more data alone insufficient when training error exceeds the desired performance level?
More data alone can bring dev error to the desired level even when training error remains above that level.
As training data increases, training error can only stay the same or _____.
Match each learning-curve element to its role in diagnosing why more data is insufficient.
Order the reasoning used to conclude that more data alone will not reach the desired performance.
Explain how the training- and dev-error curves prove that more data alone is insufficient.
Diagnose whether a team should expect more data alone to reach its desired error level.
What two observations support the conclusion that more data alone will not fix this learning curve?
Which learning-curve pattern most directly rules out more data as a sufficient solution by itself?
If training error stays unchanged as data is added, dev error can still be expected to cross below a lower desired level.