Google is committed to advancing racial equity for Black communities. See how.

More Complex Feature Crosses

Now let's play with some advanced feature cross combinations. The data set in this Playground exercise looks a bit like a noisy bullseye from a game of darts, with the blue dots in the middle and the orange dots in an outer ring.

Task 1: Run this linear model as given. Spend a minute or two (but no longer) trying different learning rate settings to see if you can find any improvements. Can a linear model produce effective results for this data set?

Task 2: Now try adding in cross-product features, such as x1x2, trying to optimize performance.

  • Which features help most?
  • What is the best performance that you can get?

Task 3: When you have a good model, examine the model output surface (shown by the background color).

  1. Does it look like a linear model?
  2. How would you describe the model?

(Answers appear just below the exercise.)