Using infix notation is exactly that - notation. There is no effect on code etc.
I also personally tend to favour the more verbose dot notation (perhaps due to
java background ). More readable IMO with the exception of DSLs where it can be
quite nice.
FWIW Spark prefers dot notation for
with that.
On 02/19/2014 08:04 AM, Nick Pentreath wrote:
I know the Spark/Mllib devs can occasionally be quite set in ways of
doing certain things, but we'd welcome as many Mahout devs as
possible
to
work together.
It may be too late, but perhaps a GSoC project to look at a port
I suspect this will be coming to Spark Mllib soon :)
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On Mon, Sep 9, 2013 at 1:40 AM, Ted Dunning ted.dunn...@gmail.com wrote:
http://arxiv.org/pdf/1107.0789v6.pdf
The basic idea is to use randomized column sampling to divide the matrix
into parts which are
Thanks for the update on that PR I will definitely take a look.
I wonder if they will run into the exact same Colt issues as mahout did?!
This DSL looks great, I'm gonna play around with it as soon as I get a chance.
One question - breeze has quite a similar syntax that is a bit simpler in
Hi Dmitry
You can take a look at using the update magic method which is similar to
apply but handles assignment.
If you want to keep the := as assignment I think you could do
def :=(value: Double) = update ...
(I don't have my laptop around at the moment so can't check this works).
That looks great Dmitry!
The thing about Breeze that drives the complexity in it is partly
specialization for Float, Double and Int matrices, and partly getting the
syntax to just work for all combinations of matrix types and operands etc.
mostly it does just work but occasionally not.
24, 2013 at 1:46 PM, Nick Pentreath
nick.pentre...@gmail.comwrote:
That looks great Dmitry!
The thing about Breeze that drives the complexity in it is partly
specialization for Float, Double and Int matrices, and partly getting the
syntax to just work for all combinations of matrix types
Hi Dmitriy
I'd be interested to look at helping with this potentially (time
permitting).
I've recently been working on a port of Mahout's ALS implementation to
Spark. I spent a bit of time thinking about how much of mahout-math to use.
For now I found that using the Breeze linear algebra
I for one have been using Spark extensively for the past few months
- admittedly not in full production, mostly for testing, prototyping - and
love it. Over the past two releases they have come a huge way, adding a
near-complete Python API and Spark Streaming (comparable to Storm - well
more like
, Mar 13, 2013 at 1:01 AM, Nick Pentreath
nick.pentre...@gmail.comwrote:
The main point of interest in this context is that I intend to build a
minimal first-cut machine learning library for Spark. This is likely to
involve porting / using parts of Mahout where it makes sense (or at the
very
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