Thank you Ted!
Do plan to do any talks in Sweden soon?
Best, Niklas
2014-04-07 14:52 GMT+02:00 Ted Dunning ted.dunn...@gmail.com:
That book is a fine beginning, but doesn't have a lot of detail.
Check out Pat's very nice demo site for more information. I have also
given a ton of talks on
On Tue, Apr 8, 2014 at 9:40 AM, Niklas Ekvall niklas.ekv...@gmail.comwrote:
Do plan to do any talks in Sweden soon?
Is last week soon enough?
:-(
That book is a fine beginning, but doesn't have a lot of detail.
Check out Pat's very nice demo site for more information. I have also
given a ton of talks on the subject.
And, to answer your question, cooccurrence recommendation works great with
diverse sources of behavior.
On Sun, Apr 6,
Hi Pat and Ted!
Yes I agree with about the rank and MAP. But in this case, that is a good
initial guess on the parameters *number of features* and *lambda*?
Where can I find the best article about cooccurrence recommender? And can
one use this approach for different types of data, e.g., ratings,
On Apr 6, 2014, at 2:48 AM, Niklas Ekvall niklas.ekv...@gmail.com wrote:
Hi Pat and Ted!
Yes I agree with about the rank and MAP. But in this case, that is a good
initial guess on the parameters *number of features* and *lambda*?
20 or 30 features depending on the variance in your data,
Thanks Pat!
I did find a book by Ted Dunning and Ellen Friedman (Practical Machine
Learning: Innovations in Recommendations) I guess I can us it to read more
about co-occurrence recommender or co-occurrence analysis.
Best, Niklas
2014-04-06 19:37 GMT+02:00 Pat Ferrel p...@occamsmachete.com:
, it doesn't much
hurt
so
you should always take as many as you can compute.
On Thu, Mar 27, 2014 at 6:33 AM, Sebastian Schelter
s...@apache.org
wrote:
Hi,
does anyone know of a principled approach of choosing the number
of
features for ALS (other
the argument that if you take too many features, it doesn't much
hurt
so
you should always take as many as you can compute.
On Thu, Mar 27, 2014 at 6:33 AM, Sebastian Schelter
s...@apache.org
wrote:
Hi,
does anyone know of a principled approach of choosing the number
of
features for ALS
, it doesn't much
hurt
so
you should always take as many as you can compute.
On Thu, Mar 27, 2014 at 6:33 AM, Sebastian Schelter
s...@apache.org
wrote:
Hi,
does anyone know of a principled approach of choosing the number
of
features for ALS (other than cross-validation
the number
of
features for ALS (other than cross-validation?)
--sebastian
--
https://github.com/bearrito
@deepbearrito
--
https://github.com/bearrito
@deepbearrito
of a principled approach of choosing the number
of
features for ALS (other than cross-validation?)
--sebastian
--
https://github.com/bearrito
@deepbearrito
--
https://github.com/bearrito
@deepbearrito
Yeah... what Pat said.
Off-line evaluations are difficult. At most, they provide directional
guidance to be refined using live A/B testing. Of course, A/B testing of
recommenders comes with a new set of tricky issues like different
recommenders learning from each other.
On Sun, Mar 30, 2014 at
Hi,
does anyone know of a principled approach of choosing the number of
features for ALS (other than cross-validation?)
--sebastian
of
features for ALS (other than cross-validation?)
--sebastian
much hurt so
you should always take as many as you can compute.
On Thu, Mar 27, 2014 at 6:33 AM, Sebastian Schelter s...@apache.org wrote:
Hi,
does anyone know of a principled approach of choosing the number of
features for ALS (other than cross-validation?)
--sebastian
the number of
features for ALS (other than cross-validation?)
--sebastian
...@apache.org
wrote:
Hi,
does anyone know of a principled approach of choosing the number of
features for ALS (other than cross-validation?)
--sebastian
--
https://github.com/bearrito
@deepbearrito
take as many as you can compute.
On Thu, Mar 27, 2014 at 6:33 AM, Sebastian Schelter s...@apache.org
wrote:
Hi,
does anyone know of a principled approach of choosing the number of
features for ALS (other than cross-validation?)
--sebastian
--
https
anyone know of a principled approach of choosing the number of
features for ALS (other than cross-validation?)
--sebastian
--
https://github.com/bearrito
@deepbearrito
--
https://github.com/bearrito
@deepbearrito
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