[mlpack-git] [mlpack/mlpack] Random projection trees (#726)

[MarcosPividori]

@lozhnikov you are right. I supposed that binary space trees always consider a splitting hyperplane, but it looks that is not true....
Well it is a bit weird... when considering RPTree-Mean, points can be splitted based on a distance to a mean point, not using a splitting hyperplane... I don't think this case would be exactly a BinarySpaceTree, it would be something different.... woudn't it?
I have quickly read the paper and I can see RPTree-Mean is defined as you implemented it. But I think there is some kind of contradiction in the paper. In a paragraph it is said:

*"On the other hand, an RPTree chooses a direction uniformly at random from the unit sphere ... and splits the data into two roughly equal-sized sets using a hyperplane orthogonal to this direction. We describe two variants, which we call RPTree-Max and RPTree-Mean. Both are adaptive to intrinsic dimension, although the proofs are in different models and use different techniques."*

So, one would expect both variants to consider a hyperplane orthogonal to this direction...


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