Yes, I was considering the accuracy as well when speaking of the
performance. (Actually put more weight to that)
I also agree with the focus on Annoys' simple usage and trade-off for
precision with query speed.
On Mon, Mar 17, 2014 at 12:33 AM, Olivier Grisel
<[email protected]>wrote:
> 2014-03-16 16:56 GMT+01:00 Maheshakya Wijewardena <[email protected]
> >:
> > Hi Olivier,
> >
> > According to the documentation of the FLANN, among the neighbor search
> > methods, there is a LSH based approach. It uses multi-probe LSH. But that
> > type of index can only be used for matching binary features using Hamming
> > distances. So the LSH-ANN used in that is not usable in general setting.
> >
> > According to
> > Radim(
> http://radimrehurek.com/2014/01/performance-shootout-of-nearest-neighbours-querying/
> )
> > ANNOYs performance is much better than FLANN.
>
> No, it rather says the opposite (look at the precision-vs-speed
> plots). Here is the conclusion by Radim:
>
> """
> FLANN is faster, but Annoy is saner. I like how it has a single
> parameter that controls accuracy that "just works". It offers pleasant
> accuracy/speed tradeoffs, a responsive developer, is memory lean,
> concise, supports mmap for sharing an index between processes (FLANN
> can only share the input matrix, and not the index itself).
> """
>
> I agree with Radim that the focus on simple usage (a nicer
> hyperparameter to tradeoff precision with query speed) is nice if the
> raw speed is comparable to the other method that has a less
> user-friendly parameterization.
>
> --
> Olivier
> http://twitter.com/ogrisel - http://github.com/ogrisel
>
>
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--
Undergraduate,
Department of Computer Science and Engineering,
Faculty of Engineering.
University of Moratuwa,
Sri Lanka
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