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
Hey @rmn0ff, great catch! Can you point out the link for the accurate reference?
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.
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
Hi @StevenJokes, we are working on that!
Just be quicker. Or can I help you? How to add these?