Thanks Kyle, this does seem to be some sort of incompatibility with the "six"
module on our Python distribution on our MacOS 10.8.
CentOS 6.3 and sklearn 0.15-git works, but not CentOS 5.2 with the same.
For now I will just use a custom build until I can figure out exactly what the
problem is.
-- Ryan
From: Kyle Kastner <[email protected]<mailto:[email protected]>>
Reply-To:
"[email protected]<mailto:[email protected]>"
<[email protected]<mailto:[email protected]>>
Date: Wednesday, October 9, 2013 11:10 AM
To:
"[email protected]<mailto:[email protected]>"
<[email protected]<mailto:[email protected]>>
Subject: Re: [Scikit-learn-general] MultinomialNB partial_fit in 0.14?
Ryan,
Default CentOS 5.2 is python 2.4-ish right? Did you install a separate Python
distribution?
I have had a lot of trouble getting Anaconda to integrate with the system
packages in CentOS - maybe this is something similar? No idea about the OSX
side of things, though.
Kyle
On Wed, Oct 9, 2013 at 12:38 PM, Ryan Rosario
<[email protected]<mailto:[email protected]>> wrote:
Three developers are working on MacOS 10.8 and CentOS 5.2 and all three of us
have the same issue on Python 2.7.
In other words, it's not just me.
Sent from my iPhone
On Oct 9, 2013, at 6:53 AM, "Jaques Grobler"
<[email protected]<mailto:[email protected]>> wrote:
I agree with Olivier -
On the latest dev version for me, partial_fit is there
I am unable to reproduce this problem
-------------------------
>>> model = naive_bayes.MultinomialNB()
>>> model.partial_fit(X, Y, classes = [0, 1])
>>> dir(model)
['__abstractmethods__', '__class__', '__delattr__', '__dict__', '__doc__',
'__format__', '__getattribute__', '__hash__', '__init__', '__module__',
'__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__',
'__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_abc_cache',
'_abc_negative_cache', '_abc_negative_cache_version', '_abc_registry',
'_count', '_get_coef', '_get_intercept', '_get_param_names',
'_joint_log_likelihood', '_update_class_log_prior', '_update_feature_log_prob',
'alpha', 'class_count_', 'class_log_prior_', 'class_prior', 'classes_',
'coef_', 'feature_count_', 'feature_log_prob_', 'fit', 'fit_prior',
'get_params', 'intercept_', 'partial_fit', 'predict', 'predict_log_proba',
'predict_proba', 'score', 'set_params']
2013/10/9 Olivier Grisel
<[email protected]<mailto:[email protected]>>
2013/10/9 Ryan Rosario <[email protected]<mailto:[email protected]>>:
> I had the same issue on a fresh clone from Git after building and
> installing it.
>
> I was able to fix the issue by removing the six.with_metaclass() call in
> the base class DiscreteNB in naive_bayes.py and then building and
> reinstalling, but this doesn't seem like a good fix for a wider audience.
>
> I filed a bug report.
>
> R.
>
> On 10/8/13 9:58 PM, "Gael Varoquaux"
> <[email protected]<mailto:[email protected]>> wrote:
>
>>On Tue, Oct 08, 2013 at 09:05:52PM +0000, Ryan Rosario wrote:
>>> I am trying to use the partial_fit function on a MultinomialNB object in
>>> 0.14-git.
>>> The API documentation for 0.14 says that this function exists. When I
>>> try to use it, I get an error:
>>
>>0.14-git is before the release of 0.14, so it might not be there yet.
Hi Ryan,
I am pretty sure you are the only one to experience this issue so it
is probably related to incorrect or not up to date install of the dev
release of scikit-learn on your side.
--
Olivier
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