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A comment on Deep Neural Decision Forests [pdf]. Parent comment

Re:Deep Neural Decision Forests [pdf] by YeGoblynQueenne on Saturday November 14, 2015 @08:46PM (#10568160)
>> One of the main theoretical results in the paper is that they propose a differentiable .. technique to optimize the parameters of the trees.

Yay! Now Decision Trees too can get stuck in local optima! :D

(totally tongue in cheek)

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Re:Deep Neural Decision Forests [pdf] by argonaut on Saturday November 14, 2015 @10:30PM (#10568367)
Even though this is tongue-in-cheek, it makes no sense. Decision trees are traditionally trained in a greedy, non-globally-optimal fashion.
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Re:Deep Neural Decision Forests [pdf] by YeGoblynQueenne on Wednesday November 18, 2015 @04:47AM (#10586841)
What I mean is that decision trees are not seen as optimising a function so it doesn't make much sense to think of them as finding optima, or getting stuck in sub-optima (if I may).

That's the traditional view. I guess it's always possible to see decision trees as optimising a binary function, but that's probably to be filed under "original research". Or maybe not- I'm not sure.

In any case, I've never heard of anyone worried that a tree learner would get stuck anywhere. The concern is usually with overfitting.

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