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Match each term to its meaning in a simple train/dev error example.
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A spam filter has 18% training error and only 19% error on the dev set. What is the best description of this model?
When a model has high bias and low variance, the training error is usually much lower than the dev error because the model is overfitting.
A model that does not match the training data well and generalizes poorly is said to have high bias and low _____.
Match each term to its meaning in a simple train/dev error example.
Order the steps for estimating bias and variance in a classifier.
What does an estimated variance of 2% indicate when the estimated bias is 12%?
A model that underfits usually has low training error and much higher dev error.
Estimating Bias from Training Error
Link the fit pattern to what it says about a model
Arrange the reasoning steps that show a classifier with 18% training error and a 1% train-dev gap is underfitting.
Explain what 12% bias and 2% variance imply for a classifier.
Evaluating a loan default model with weak training performance.
What is the name for a model that is too simple to fit the patterns in the data well?