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A data mismatch problem means the model performs poorly on both training-like data and the development/test data.
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Recognizing Distribution Mismatch from Error Measurements
Collect Training Examples That Resemble the Hard Development Cases
Compare training and development data properties after a mismatch is found
What best describes a mismatch between training data and evaluation data?
A data mismatch problem means the model performs poorly on both training-like data and the development/test data.
Data mismatch and distribution fit
Match each data-distribution term with its description.
Put the diagnostic workflow for dataset shift in the correct order.
What most directly causes a mismatch between training data and evaluation data?
A voice-to-text system can perform well on the training set and training-dev set but still do poorly on the dev set if the dev data comes from a different distribution.
Training Distribution and Evaluation Distribution
Match each performance pattern to the most likely diagnosis of the model's problem.
Put the steps in order for diagnosing a distribution mismatch from model performance.
Explain what a performance gap across two data distributions suggests
Explain why a voice-command model looks strong on one split but weak on another.
Why is this called data mismatch?