On Tue, Mar 14, 2017 at 08:23:20PM +0300, Сидоров Константин wrote: >> That's right the HAM module uses a fixed memory size and the >> gist looks clean and minimal, however, I would also take a look >> at the existing mlpack implementations. If we implement some >> tree that we use for the HAM model we have to make sure it's >> well tested and that sometimes takes more time than the actual >> implementation; if we could reuse some existing code, it's >> already tested. But as I said, if it turns out implementing some >> specific structure is a better way, we can do that. No need to >> use some code that wasn't designed to be used in a totally >> different way. > > I looked in core/tree directory > ([2]https://github.com/mlpack/mlpack/tree/master/src/mlpack/core/tree). > There are some tree structures, but I can't see a good way to adapt > them to HAM architecture - but even if there is, I think it still > will be more convenient to implement the gist of my previous > letter. The reason is that tree structures from core/tree are > created with different problems in mind and maintain > problem-specific information in them, which is definitely not going > to help because it will hinder both execution and developer time. > Maybe I was just unable to find the right tree structure - if so, > give me a link to it, because (as you mentioned) having a ready and > tested implementation is helpful.
I agree---I don't think mlpack's trees are suited to the HAM situation. In HAM, my understanding is that a specialized binary tree structure (built on 1-dimensional data) is used, and the tree is traversed probabilistically to find the attended/accessed leaf. The mlpack trees are built for multidimensional data, though, so I am not sure if there is an easy way to adapt it. It probably would be better to either implement a specialized structure or see if something in std:: would be usable. But I think because of the way it will be traversed, it may be somewhat difficult to use some std:: object... maybe it is possible though. -- Ryan Curtin | "I'm just going to shoot you once!" [email protected] | - Joseph Dunn _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
