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Diagnosing High Avoidable Bias from Similar Error Rates
If a model records 10% error on the training set, 11% on the training-development split, and 12% on the development set, the main diagnosis is high avoidable bias. This means the model is not fitting the training data well.
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Learn After
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.
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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.
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