# FAQ: Random Forests - Classify

This community-built FAQ covers the “Classify” exercise from the lesson “Random Forests”.

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The list of predictions have `None` as elements inside it. I am confused why it is so?

Thanks a lot!

3 Likes

I put the following code inside the for loop to print trees which classified `unlabeled_point` as `None`.

``````for i in range(20):
...

prediction = classify(unlabeled_point, subset_tree)

if prediction is None:
print_tree(subset_tree)
``````

Then I found that the displayed trees cannot actually classify the `unlabeled_point` (because there are not enough branches). Depending on subset of data it seems possible that the given function `build_tree()` creates such a tree.

why we use random.seed().Can anyone explain please?thanks you!

If we use the same random.seed, we can reproduce the same results. It is random, but it is the SAME random.

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thanks you a lot:)!!!

1 Like