Hello,
The regression module will require a lot of linear math, specifically matrix operations which I’ve heard is outdated. Are there any updates on it’s development? Is this someone’s GSoC project? If not I could try to help by attempting to start porting regression essential operations. But the dependencies for the current library is vast so this would end up being a large endeavor and I know I am not one to properly design a linear math library, I only know the basics, it would probably become a mess. So if there is no current development plan I fear I might have to start by using the old library for now until linear’s development kicks in…. Is this okay? Thank you, Ben |
> On May 8, 2019, at 4:37 PM, Ben Nguyen <[hidden email]> wrote: > > Hello, > > The regression module will require a lot of linear math, specifically matrix operations which I’ve heard is outdated. Are there any updates on it’s development? Is this someone’s GSoC project? If not I could try to help by attempting to start porting regression essential operations. But the dependencies for the current library is vast so this would end up being a large endeavor and I know I am not one to properly design a linear math library, I only know the basics, it would probably become a mess. So if there is no current development plan I fear I might have to start by using the old library for now until linear’s development kicks in…. Is this okay? > I suppose the question is: what is commons-numbers, and if a matrix is a “number” or it is sufficiently different to warrant a separate component. It is worth noting that in there have been past arguments over additional math components before we get 1.0 releases for the current ones in flight (but I feel like the fastest route to any component’s 1.0 should take priority). What are other folks’ thoughts here? I would think that linear algebra would likely be a widely used library as it’s fairly fundamental to a collection of machine learning algorithms as they are based in least squares. -Rob > Thank you, > Ben --------------------------------------------------------------------- To unsubscribe, e-mail: [hidden email] For additional commands, e-mail: [hidden email] |
It looks to me like the EJML library is the best choice for linear algebra
right now, is well supported, and we should not reinvent the wheel unless we have the motivation and expertise to do so. EJML is under the Apache 2.0 license which I read to mean we can use it in any derivative way we please so long as (and this would be true regardless if the license requires it IMO) we attribute the source. So as a default plan I would shade these libraries within the regression module, with thanks and attribution to the EJML site and org. On Wed, May 8, 2019 at 2:49 PM Rob Tompkins <[hidden email]> wrote: > > > > On May 8, 2019, at 4:37 PM, Ben Nguyen <[hidden email]> wrote: > > > > Hello, > > > > The regression module will require a lot of linear math, specifically > matrix operations which I’ve heard is outdated. Are there any updates on > it’s development? Is this someone’s GSoC project? If not I could try to > help by attempting to start porting regression essential operations. But > the dependencies for the current library is vast so this would end up being > a large endeavor and I know I am not one to properly design a linear math > library, I only know the basics, it would probably become a mess. So if > there is no current development plan I fear I might have to start by using > the old library for now until linear’s development kicks in…. Is this okay? > > > > I suppose the question is: what is commons-numbers, and if a matrix is a > “number” or it is sufficiently different to warrant a separate component. > > It is worth noting that in there have been past arguments over additional > math components before we get 1.0 releases for the current ones in flight > (but I feel like the fastest route to any component’s 1.0 should take > priority). > > What are other folks’ thoughts here? I would think that linear algebra > would likely be a widely used library as it’s fairly fundamental to a > collection of machine learning algorithms as they are based in least > squares. > > -Rob > > > Thank you, > > Ben > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [hidden email] > For additional commands, e-mail: [hidden email] > > |
Hi.
Le mer. 8 mai 2019 à 23:59, Eric Barnhill <[hidden email]> a écrit : > > It looks to me like the EJML library is the best choice for linear algebra https://lessthanoptimal.github.io/Java-Matrix-Benchmark/runtime/2019_02_i53570/ > right now, is well supported, and we should not reinvent the wheel +1 > unless > we have the motivation and expertise to do so. Quite unlikely to be done in time for it to be useful to the GSoC assignment. > > EJML is under the Apache 2.0 license which I read to mean we can use it in > any derivative way we please so long as (and this would be true regardless > if the license requires it IMO) we attribute the source. > > So as a default plan I would shade these libraries within the regression > module, +1 It may be prudent to delineate an interface between "Commons" and the linear algebra functionalities providers (cf. list in the above link), so that we can switch from one to another and analyze the impact of doing so. Regards, Gilles > with thanks and attribution to the EJML site and org. > > > On Wed, May 8, 2019 at 2:49 PM Rob Tompkins <[hidden email]> wrote: > > > > > > > > On May 8, 2019, at 4:37 PM, Ben Nguyen <[hidden email]> wrote: > > > > > > Hello, > > > > > > The regression module will require a lot of linear math, specifically > > matrix operations which I’ve heard is outdated. Are there any updates on > > it’s development? Is this someone’s GSoC project? If not I could try to > > help by attempting to start porting regression essential operations. But > > the dependencies for the current library is vast so this would end up being > > a large endeavor and I know I am not one to properly design a linear math > > library, I only know the basics, it would probably become a mess. So if > > there is no current development plan I fear I might have to start by using > > the old library for now until linear’s development kicks in…. Is this okay? > > > > > > > I suppose the question is: what is commons-numbers, and if a matrix is a > > “number” or it is sufficiently different to warrant a separate component. > > > > It is worth noting that in there have been past arguments over additional > > math components before we get 1.0 releases for the current ones in flight > > (but I feel like the fastest route to any component’s 1.0 should take > > priority). > > > > What are other folks’ thoughts here? I would think that linear algebra > > would likely be a widely used library as it’s fairly fundamental to a > > collection of machine learning algorithms as they are based in least > > squares. > > > > -Rob > > > > > Thank you, > > > Ben > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: [hidden email] > > For additional commands, e-mail: [hidden email] > > > > --------------------------------------------------------------------- To unsubscribe, e-mail: [hidden email] For additional commands, e-mail: [hidden email] |
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