What type of bias is suggested when training error stays high?
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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
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