On Tue, Dec 27, 2011 at 6:23 PM, Olivier Grisel
wrote:
> Hi all,
>
> I came across the following blog post about Andrew Ng's ML class and I
> like the training / validation errors plots to find out whether the
> model is too biased (underfitting) or two lax (high variance,
> over-fitting).
>
> ht
In that case, It can also be applied to Chinese word segmentation.
On Wed, Dec 28, 2011 at 6:49 AM, Lars Buitinck wrote:
> 2011/12/27 Nelle Varoquaux :
> > VDHMMs are HMMs in which a state can emit a serie of observations. It
> seems
> > that the main application to these chains are speech recog
2011/12/27 Nelle Varoquaux :
> VDHMMs are HMMs in which a state can emit a serie of observations. It seems
> that the main application to these chains are speech recognition, and
> handwriting recognition: fields in which we are trying to determine a state
> to poorly segmented data. Would anyone k
On Tue, Dec 27, 2011 at 4:36 PM, Nelle Varoquaux
wrote:
> Hi all,
>
> Despite this not being directly related to scikit-learn, I hope to benefit
> from the experience of machine learning developpers:
> I'm currently studying an article on Variable Duration HMMs (VDHMMs), and I
> am seeking advices
Hi all,
Despite this not being directly related to scikit-learn, I hope to benefit
from the experience of machine learning developpers:
I'm currently studying an article on Variable Duration HMMs (VDHMMs), and I
am seeking advices on application data.
VDHMMs are HMMs in which a state can emit a s
Hi all,
I came across the following blog post about Andrew Ng's ML class and I
like the training / validation errors plots to find out whether the
model is too biased (underfitting) or two lax (high variance,
over-fitting).
http://digitheadslabnotebook.blogspot.com/2011/12/practical-advice-for
Hi Andy,
On 27 December 2011 13:37, Andreas Müller wrote:
> Hi everybody!
> I was wondering if anyone is working on ensemble meta-estimators.
> There seems to have been some effort by @glouppe when doing the random
> forests.
> Is that still going on?
I am not working on that currently.
> Also,
Hi everybody!
I was wondering if anyone is working on ensemble meta-estimators.
There seems to have been some effort by @glouppe when doing the random
forests.
Is that still going on?
Also, I was wondering how tree-specific the random forest module is.
I looked at the pull request but could not f
Please comment here:
https://github.com/scikit-learn/scikit-learn/pull/515
--
Olivier
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