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30 Interpreting learning curves: High bias

Suppose your dev error curve looks like this:

We previously said that, if your dev error curve plateaus, you are unlikely to achieve the
desired performance just by adding data.

But it is hard to know exactly what an extrapolation of the red dev error curve will look like.

If the dev set was small, you would be even less certain because the curves could be noisy.

Suppose we add the training error curve to this plot and get the following:

Now, you can be absolutely sure that adding more data will not, by itself, be sufficient. Why
is that? Remember our two observations:

Page 60 Machine Learning Yearning-Draft Andrew Ng