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mblondel opened this issue Nov 5, 2012 · 19 comments · Fixed by #3317
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model persistence documentation #1332

mblondel opened this issue Nov 5, 2012 · 19 comments · Fixed by #3317
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Documentation Easy Well-defined and straightforward way to resolve
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0.15

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@mblondel
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mblondel commented Nov 5, 2012

How to save a model (i.e., model persistence) used to be a sub-section of the tutorial and visible directly from the homepage. But since now it's become a sub-sub-section, it's not visible anymore.

Since it's a very common need it would be nice to make it more prominent. Maybe a section of its own?
@zaxtax
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zaxtax commented Nov 7, 2012

+1

@ogrisel
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ogrisel commented Nov 7, 2012

+1 too

@AWinterman
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+1 :)

@vene
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vene commented Jan 6, 2013

Moving just model persistence at the highest level would be a bit out of place. Moving it as a child of a top-level section would be OK, but no current section would accomodate it nicely.

The most elegant thing in my opinion would be move /tutorials/basic_tutorial to /quick_start and saving the tutorials section for in-depth, multi-page ones. Any better ideas?

@amueller
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amueller commented Jan 6, 2013

Having a "Quick start" section sounds good. The two things under "tutorials" are really quite different in nature.
The old tutorial as quick start could be a good thing to reference for lazy people asking questions on the ml ;)
I can totally understand that someone getting started doesn't want to go through all of the statistical learning tutorial.

@vene
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vene commented Jan 6, 2013

At the moment, Model Persistence is just a paragraph and that's a bit small for a top-level module. Alternatively, instead of my "Quick Start" suggestion, we could indeed push it up but rename it to something like "Deploying a trained model" and explore it in more detail, like also pointing out how this could sometimes be done avoiding the scikit-learn dependency (I remember this question popping up too)? And also show some real comparison of pickling with cPickle vs joblib (timing, disk usage)?

@jaquesgrobler
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So what's the verdict on this issue?
One thing - moving the basic tutorial out of the Tutorials section and into a Quick start section sounds good and would definitely be quick and easy, but won't the other tutorial look a tad lonely then? (Not that that is a major issue).. @vene 's second suggestion also sounds good to me

@vene
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vene commented Jan 11, 2013

Wasn't there another tutorial that we were planning to merge? This would
make the big one less lonely :)

On Fri, Jan 11, 2013 at 2:11 PM, Jaques Grobler notifications@github.comwrote:

So what's the verdict on this issue?
One thing - moving the basic tutorial out of the Tutorials section and
into a Quick start section sounds good and would definitely be quick and
easy, but won't the other tutorial look a tad lonely then? (Not that that
is a major issue).. @vene https://github.com/vene 's second suggestion
also sounds good to me

—
Reply to this email directly or view it on GitHubhttps://github.com//issues/1332#issuecomment-12145498.

@jaquesgrobler
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Hmm good question.. perhaps they were the external tutorials (the astro and neuroimg ones). Can't think of any other ones.. @amueller @GaelVaroquaux You guys maybe know?

@amueller
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There is @ogrisel's on text processing but I think that is pretty out of date.

@ogrisel
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ogrisel commented Jan 12, 2013

The narrative doc on text feature expression is now good enough even though it does not feature how to pipeline it with a classifier (but there is an example).

@amueller
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OT @ogrisel the tutorial is still online and uses an old api, right? maybe you should take it down. I got questions about it on IRC recently.

@amueller
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Reassigned to next release as I don't really see a consent.

@ogrisel
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ogrisel commented Jan 21, 2013

I will open a new issue to reintegrate / update the text data processing part of the tutorial into a new tutorial section in the scikit-learn narrative documentation. The rest of the tutorial can be dropped as redundant.

@amueller
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Thanks :)

@amueller
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retagging 0.14

@GaelVaroquaux
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No progress. Retagging.

@kaushik94
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i guess i can do a PR for this.
shall i go with the "quick start" model or any other ideas are to be considered ?

@raulgarreta raulgarreta mentioned this issue Apr 17, 2014
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@pignacio pignacio mentioned this issue Jun 26, 2014
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@jnothman
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Fixed by #3317

@jnothman jnothman reopened this Jun 27, 2014
@jnothman jnothman mentioned this issue Sep 30, 2014
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[MRG+2] Model persistence doc pignacio/scikit-learn
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@zaxtax @jnothman @ogrisel @GaelVaroquaux @mblondel @vene @amueller @AWinterman @jaquesgrobler @kaushik94
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