If the features of Model 1 are a strict subset of those in Model 2, which model will USUALLY have lower TRAINING error?Group of answer choicesIt's impossible to tell with only this informationModel 2Model 1
Question
If the features of Model 1 are a strict subset of those in Model 2, which model will USUALLY have lower TRAINING error?Group of answer choicesIt's impossible to tell with only this informationModel 2Model 1
Solution
Model 2 will usually have a lower training error. This is because Model 2 includes all the features of Model 1 and possibly additional features. More features can allow the model to fit the training data more closely, thus potentially reducing the training error. However, it's important to note that while a lower training error might sound beneficial, it could also lead to overfitting, where the model performs well on the training data but poorly on unseen data.
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