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[ 4 pts ] If we choose the model with minimum training error, explain why we most likely choose the most complex model ( the

[4 pts] If we choose the model with minimum training error, explain
why we most likely choose the most complex model (the curve in orange).
Explain it using the following figure.
[4 pts] From p.11&12 in slides, explain why minimizing w2 actually has effect of making the model
simpler.
[4 pts] You model has a high test error. You want to know whether your model has the problem of
overfitting or underfitting. How do we know this? (Refer to p.24 in slides) Explain the reason.
[4 pts] Explain two data augmentation methods for text data. (2-3 lines)
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