Apologies for letting this slide... way too much life got in the way :)
> On Mar 3, 2017, at 3:36 PM, Dmitriy Lyubimov wrote:
>
> And by formula yes i mean R syntax.
>
> possible use case would be to take Spark DataFrame and formula (say, `age ~
> . -1`) and produce outputs of DrmLike[Int] (a d
And by formula yes i mean R syntax.
possible use case would be to take Spark DataFrame and formula (say, `age ~
. -1`) and produce outputs of DrmLike[Int] (a distributed matrix type) that
converts into predictors and target.
In this particular case, this formula means that the predictor matrix (X
On Fri, Mar 3, 2017 at 4:09 AM, Jim Jagielski wrote:
>
>>
>>
>
>> >
>> > 3) On the feature extraction per R like formula can you elaborate more
>> here, are you talking about feature extraction using R like dataframes and
>> operators?
>>
>
>
Yes. I would start doing generic formula parser and the
I am getting a liittle bit lost who asked what here, inline.
On Fri, Mar 3, 2017 at 4:09 AM, Jim Jagielski wrote:
>
>
> Would it make sense to keep them as-is, and "pull them out", as
> it were, should they prove to be wanted/needed by the other algo users?
>
I would hope it is of some help (es
hrough the papers.
>
>
>
> From: Dmitriy Lyubimov
> Sent: Friday, February 17, 2017 1:45 PM
> To: dev@mahout.apache.org
> Subject: Re: Contributing an algorithm for samsara
>
> in particular, this is the samsara implementation of do
m: Dmitriy Lyubimov
Sent: Friday, February 17, 2017 1:45 PM
To: dev@mahout.apache.org
Subject: Re: Contributing an algorithm for samsara
in particular, this is the samsara implementation of double-weighed als :
https://github.com/apache/mahout/pull/14/files#diff-0fbeb8b848ed0c5e3f782c72569cf626
M
extraction per (preferrably R-like) formula.
>
>
> -d
>
>
> On Fri, Feb 17, 2017 at 10:11 AM, Andrew Palumbo
> wrote:
>
>> +1 to glms
>>
>>
>>
>> Sent from my Verizon Wireless 4G LTE smartphone
>>
>>
>>
l message
> From: Trevor Grant
> Date: 02/17/2017 6:56 AM (GMT-08:00)
> To: dev@mahout.apache.org
> Subject: Re: Contributing an algorithm for samsara
>
> Jim is right, and I would take it one further and say, it would be best to
> implement GLMs https://en.wikipedi
+1 to glms
Sent from my Verizon Wireless 4G LTE smartphone
Original message
From: Trevor Grant
Date: 02/17/2017 6:56 AM (GMT-08:00)
To: dev@mahout.apache.org
Subject: Re: Contributing an algorithm for samsara
Jim is right, and I would take it one further and say, it would
lgorithms, what do you think?
Regards
From: Jim Jagielski
Sent: Friday, February 17, 2017 8:18 AM
To: dev@mahout.apache.org
Subject: Re: Contributing an algorithm for samsara
Sounds good to me. +1
> On Feb 17, 2017, at 11:15 AM, Saikat Kanjilal wrote:
>
> Jim,
> What do you say we s
Sounds good to me. +1
> On Feb 17, 2017, at 11:15 AM, Saikat Kanjilal wrote:
>
> Jim,
> What do you say we start with ALS and then tackle glm?
>
>
> Sent from my iPhone
>
>> On Feb 17, 2017, at 6:56 AM, Trevor Grant wrote:
>>
>> Jim is right, and I would take it one further and say, it woul
Jim,
What do you say we start with ALS and then tackle glm?
Sent from my iPhone
> On Feb 17, 2017, at 6:56 AM, Trevor Grant wrote:
>
> Jim is right, and I would take it one further and say, it would be best to
> implement GLMs https://en.wikipedia.org/wiki/Generalized_linear_model ,
> from the
Jim is right, and I would take it one further and say, it would be best to
implement GLMs https://en.wikipedia.org/wiki/Generalized_linear_model ,
from there a Logistic regression is a trivial extension.
Buyer beware- GLMs will be a bit of work- doable, but that would be jumping
in neck first for
My own thoughts are that logistic regression seems a more "generalized"
and hence more useful algo to be factored in... At least in the
use cases that I've been toying with.
So I'd like to help out with that if wanted...
> On Feb 9, 2017, at 3:59 PM, Saikat Kanjilal wrote:
>
> Trevor et al,
>
Trevor et al,
I'd like to contribute an algorithm or two in samsara using spark as I would
like to do a compare and contrast with mahout with R server for a data science
pipeline, machine learning repo that I'm working on, in looking at the list of
algorithms (https://mahout.apache.org/users/ba
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