Learn Before
Some Simpler Models Stop Improving Much After More Data
Models such as logistic regression can reach a point where adding more labeled examples brings little or no extra improvement. At that stage, the learning curve becomes nearly flat, so extra data no longer changes performance much.
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Some Simpler Models Stop Improving Much After More Data
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Learn After
What often happens to an older algorithm as more and more data is added?
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Recognizing when a model stops improving
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A stalled learning curve indicates a plateau