Diagnosing Error Sources from Training and Development Gaps
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What does a pattern of 10% training error, 11% training-dev error, and 12% dev error most strongly suggest?
High training error signals poor fit on the training set
What type of bias is suggested when training error stays high?
Match each error metric in this classifier-debugging scenario to its correct value or diagnosis.
Diagnose High Bias from Three Error Rates
What does a tiny gap between training error and training-dev error indicate?
A model with 10% error on training data, 11% error on a training-like holdout set, and 12% error on the development set is mainly overfitting.
If training error is far worse than training-dev error, the model is doing poorly on the _____ set.
Diagnosing Error Sources from Training and Development Gaps
Diagnosing a High-Bias Model from Three Similar Error Rates
What a 10% train error, 11% train-dev error, and 12% dev error reveal
Diagnosing a model with 14% training error, 15% train-dev error, and 16% dev error
Recognizing the Bias Pattern in the Error Rates