https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/statistics.html
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If a model suffers from high bias error, we often say it is underfitting or lack of generalization
If a model suffers from high variance, we often say it is overfitting and lack of flexibility
I think the characteristics of a high bias model and a high variance model are mixed up here. I believe that a high bias model lacks of flexibility while a high variance model lacks of generalization
.
https://keras.rstudio.com/articles/tutorial_overfit_underfit.html
I agree that a high variance model lacks of
generalization
, if it means that the model doesn’t work in other patterns.But I still feel confused about the meaning of flexibility, if it means that the model doesn’t work in these data, then @rmn0ff is right.
Page 7:
Now, I think @rmn0ff is right.
I notice that we don’t have the corresponding discussion of pytorch and tensorflow versions to last chapters.
And I tried to add some. Is it right? @astonzhang, @goldpiggy
https://discuss.d2l.ai/t/how-to-create-a-discussion-about-the-books-chapter/552/3
Just be quicker. Or can I help you? How to add these?