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Informal meaning of bias in a large-sample setting
In informal machine-learning language, an algorithm's _____ is the training-set error it would have if the training data were extremely large.
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Informal Meaning of Model Bias
True or False: In this framework, the term bias refers to a model’s error on the validation or test set.
Informal meaning of bias in a large-sample setting
Informal Meaning of Bias
In this informal usage, bias means the model's error on the training set.
Informally, an algorithm's _____ is the error rate on the training set.
Match each learning-curve term to its meaning.
Order the steps for estimating bias from training error.
Why use a very large training set when estimating bias?
Bias Is Measured on the Holdout Set
In the large-sample limit, bias is typically assessed on the _____ data.
Match each learning-term description with its role in the informal bias definition.
Order the steps for deciding whether bias is the main cause of poor model performance.
How Informal Bias Relates to Training Error
Interpreting Training Error on a Large Dataset
Informal Bias and Training Error