Andy,
I just recently discussed this with Gilles; There are a number of
things involved here: Gilles told me that his experience shows that
randomized trees are usually deeper than regular trees thus the
increased training time.
After looking at the code I also found that ``_find_random_split``
r
> We're happy to announce the 6th version of scikits-image!
Congratulations! It is nice to see scikits-image threading along.
Gael
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Announcement: scikits-image 0.6
===
We're happy to announce the 6th version of scikits-image!
Scikits-image is an image processing toolbox for SciPy that includes algorithms
for segmentation, geometric transformations, color space manipulation,
analysis, filtering, mor
I just read the Post and i was wodering: shouldn't extra trees be faster than
random forests? In the Blog Post they are slower.
Andy
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Olivier Grisel schrieb:
Here is the link:
http://blog.explainmydata.com/2012/0
For posterity, this the written consent for the "load_kalman_data" dataset
that will (hopefully) be integrated in the sklearn soon.
Daniel Duckworth
-- Forwarded message --
From: Daniel Duckworth
Date: Wed, May 16, 2012 at 11:59 AM
Subject: Re: Fall CS287 HW2 Dataset
To: Pieter
Hi Alexandre,
>> 2. alphas should be sorted in ascending order? Or at least sorted?
>
> no. The path is fit starting from high alpha so alphas are returns in
> decreasing order.
Okay, thanks. I have an instance where this list of values is not
sorted. I'll submit a bug report.
--
Cp
---
2012/6/24 Mathieu Blondel :
> It's important to bear in mind that some parameters have a huge impact on
> performance and that just using the default ones may result in unfair
> comparisons. For example, SGDClassifier uses the quite small n_iter=5 by
> default whereas liblinear-based algorithms che
It's important to bear in mind that some parameters have a huge impact on
performance and that just using the default ones may result in unfair
comparisons. For example, SGDClassifier uses the quite small n_iter=5 by
default whereas liblinear-based algorithms check that the solution is close
enough
2012/6/24 Lars Buitinck :
> 2012/6/24 Olivier Grisel :
>> I find stackoverflow a good way to answer questions and they are very
>> well indexed in search engine (much better than the mailing list
>> archives for instance) and the vote system makes it easy to find the
>> most useful answers / commen
2012/6/24 Olivier Grisel :
> I find stackoverflow a good way to answer questions and they are very
> well indexed in search engine (much better than the mailing list
> archives for instance) and the vote system makes it easy to find the
> most useful answers / comments. At some point we will also b
Hi all,
I spent a bunch of time re-tagging the questions about scikit-learn on
stackoverflow so that the new scikit-learn tag will be used by news
user in a more consistent way:
http://stackoverflow.com/questions/tagged/scikit-learn?pagesize=50
If you would like to support our users by answering
Here is the link:
http://blog.explainmydata.com/2012/06/ntrain-24853-ntest-25147-ncorrupt.html
--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel
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Emanuele,
I just realized that the above approach might not be what you actually
want: It will select the best value for ``n_estimators`` for _each_
fold - what we actually should do is to average the staged scores over
all folds and select the ``n_estimators`` which has the best average
score.
I
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