From tmrsg11 at gmail.com  Mon Apr  5 10:35:48 2021
From: tmrsg11 at gmail.com (C W)
Date: Mon, 5 Apr 2021 10:35:48 -0400
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
Message-ID: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>

Hello all,

I can't install pip on this computer. It has conda installed (probably not
helpful). Is there a work around to install XGBoost and packages?

I remember reading on stackoverflow, there were some simple commands to do
it. I actually used it to install packages without pip.

I can't find the post anymore, could anyone help?

Thanks so much!

Mike
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From tmrsg11 at gmail.com  Mon Apr  5 10:54:21 2021
From: tmrsg11 at gmail.com (C W)
Date: Mon, 5 Apr 2021 10:54:21 -0400
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
In-Reply-To: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
References: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
Message-ID: <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>

Hello again,

I have 3 follow-up questions.

1) Upon searching, Anaconda website (
https://anaconda.org/anaconda/py-xgboost) says that you can install with,
> conda install -c anaconda py-xgboost
I have miniconda, not anaconda, I guess I just replace it anaconda with
minconda?

2) Using pip3 command,
> pip3 install xgboost
I don't have pip.

3) From XGBoost website, I now see that you can build XGBoost from source (
https://xgboost.readthedocs.io/en/latest/build.html)

Question: will all the 3 methods install XGBoost in the same folder?

Thanks a lot!

On Mon, Apr 5, 2021 at 10:35 AM C W <tmrsg11 at gmail.com> wrote:

> Hello all,
>
> I can't install pip on this computer. It has conda installed (probably not
> helpful). Is there a work around to install XGBoost and packages?
>
> I remember reading on stackoverflow, there were some simple commands to do
> it. I actually used it to install packages without pip.
>
> I can't find the post anymore, could anyone help?
>
> Thanks so much!
>
> Mike
>
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From tmrsg11 at gmail.com  Mon Apr  5 11:26:56 2021
From: tmrsg11 at gmail.com (C W)
Date: Mon, 5 Apr 2021 11:26:56 -0400
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
In-Reply-To: <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>
References: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
 <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>
Message-ID: <CAE2FW2=YAvDEPkdJh6fp+ZjjiQmDFypUWgUDBDtSs=6LqOAscw@mail.gmail.com>

Update:

It seems I've already installed XGBoost before. But, I get the following
error:

>>> import xgboost
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File
"/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/__init__.py",
line 9, in <module>
    from .core import DMatrix, DeviceQuantileDMatrix, Booster
  File
"/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
line 174, in <module>
    _LIB = _load_lib()
  File
"/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
line 157, in _load_lib
    raise XGBoostError(
xgboost.core.XGBoostError: XGBoost Library (libxgboost.dylib) could not be
loaded.
Likely causes:
  * OpenMP runtime is not installed (vcomp140.dll or libgomp-1.dll for
Windows, libomp.dylib for Mac OSX, libgomp.so for Linux and other UNIX-like
OSes). Mac OSX users: Run `brew install libomp` to install OpenMP runtime.
  * You are running 32-bit Python on a 64-bit OS
Error message(s):
['dlopen(/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib,
6): Library not loaded: /usr/local/opt/libomp/lib/libomp.dylib\n
 Referenced from:
/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib\n
 Reason: image not found']

It seems OpenMP runtime the one I am missing. I can install by running
> brew install libomp

But, I don't have brew on this computer. Any work around?

Thanks!

On Mon, Apr 5, 2021 at 10:54 AM C W <tmrsg11 at gmail.com> wrote:

> Hello again,
>
> I have 3 follow-up questions.
>
> 1) Upon searching, Anaconda website (
> https://anaconda.org/anaconda/py-xgboost) says that you can install with,
> > conda install -c anaconda py-xgboost
> I have miniconda, not anaconda, I guess I just replace it anaconda with
> minconda?
>
> 2) Using pip3 command,
> > pip3 install xgboost
> I don't have pip.
>
> 3) From XGBoost website, I now see that you can build XGBoost from source (
> https://xgboost.readthedocs.io/en/latest/build.html)
>
> Question: will all the 3 methods install XGBoost in the same folder?
>
> Thanks a lot!
>
> On Mon, Apr 5, 2021 at 10:35 AM C W <tmrsg11 at gmail.com> wrote:
>
>> Hello all,
>>
>> I can't install pip on this computer. It has conda installed (probably
>> not helpful). Is there a work around to install XGBoost and packages?
>>
>> I remember reading on stackoverflow, there were some simple commands to
>> do it. I actually used it to install packages without pip.
>>
>> I can't find the post anymore, could anyone help?
>>
>> Thanks so much!
>>
>> Mike
>>
>
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From nicholdav at gmail.com  Mon Apr  5 12:04:14 2021
From: nicholdav at gmail.com (David Nicholson)
Date: Mon, 5 Apr 2021 12:04:14 -0400
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
In-Reply-To: <CAE2FW2=YAvDEPkdJh6fp+ZjjiQmDFypUWgUDBDtSs=6LqOAscw@mail.gmail.com>
References: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
 <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>
 <CAE2FW2=YAvDEPkdJh6fp+ZjjiQmDFypUWgUDBDtSs=6LqOAscw@mail.gmail.com>
Message-ID: <CAMabFbVjAHSG2TSCMnQUnmK9C0DHy89590ZWxpTwPetmZODULw@mail.gmail.com>

You might find more people that can help with other libraries such as
XGBoost and conda on stack overflow, a list dedicated to those tools, or
their github repositories.
https://discuss.xgboost.ai/
https://groups.google.com/a/continuum.io/g/conda

David Nicholson, Ph.D.
https://nicholdav.info/
https://github.com/NickleDave
Prinz lab <http://www.biology.emory.edu/research/Prinz/>, Emory University,
Atlanta, GA, USA


On Mon, Apr 5, 2021 at 11:28 AM C W <tmrsg11 at gmail.com> wrote:

> Update:
>
> It seems I've already installed XGBoost before. But, I get the following
> error:
>
> >>> import xgboost
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
>   File
> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/__init__.py",
> line 9, in <module>
>     from .core import DMatrix, DeviceQuantileDMatrix, Booster
>   File
> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
> line 174, in <module>
>     _LIB = _load_lib()
>   File
> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
> line 157, in _load_lib
>     raise XGBoostError(
> xgboost.core.XGBoostError: XGBoost Library (libxgboost.dylib) could not be
> loaded.
> Likely causes:
>   * OpenMP runtime is not installed (vcomp140.dll or libgomp-1.dll for
> Windows, libomp.dylib for Mac OSX, libgomp.so for Linux and other UNIX-like
> OSes). Mac OSX users: Run `brew install libomp` to install OpenMP runtime.
>   * You are running 32-bit Python on a 64-bit OS
> Error message(s):
> ['dlopen(/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib,
> 6): Library not loaded: /usr/local/opt/libomp/lib/libomp.dylib\n
>  Referenced from:
> /Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib\n
>  Reason: image not found']
>
> It seems OpenMP runtime the one I am missing. I can install by running
> > brew install libomp
>
> But, I don't have brew on this computer. Any work around?
>
> Thanks!
>
> On Mon, Apr 5, 2021 at 10:54 AM C W <tmrsg11 at gmail.com> wrote:
>
>> Hello again,
>>
>> I have 3 follow-up questions.
>>
>> 1) Upon searching, Anaconda website (
>> https://anaconda.org/anaconda/py-xgboost) says that you can install with,
>> > conda install -c anaconda py-xgboost
>> I have miniconda, not anaconda, I guess I just replace it anaconda with
>> minconda?
>>
>> 2) Using pip3 command,
>> > pip3 install xgboost
>> I don't have pip.
>>
>> 3) From XGBoost website, I now see that you can build XGBoost from source
>> (https://xgboost.readthedocs.io/en/latest/build.html)
>>
>> Question: will all the 3 methods install XGBoost in the same folder?
>>
>> Thanks a lot!
>>
>> On Mon, Apr 5, 2021 at 10:35 AM C W <tmrsg11 at gmail.com> wrote:
>>
>>> Hello all,
>>>
>>> I can't install pip on this computer. It has conda installed (probably
>>> not helpful). Is there a work around to install XGBoost and packages?
>>>
>>> I remember reading on stackoverflow, there were some simple commands to
>>> do it. I actually used it to install packages without pip.
>>>
>>> I can't find the post anymore, could anyone help?
>>>
>>> Thanks so much!
>>>
>>> Mike
>>>
>> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From tmrsg11 at gmail.com  Tue Apr  6 17:59:25 2021
From: tmrsg11 at gmail.com (C W)
Date: Tue, 6 Apr 2021 17:59:25 -0400
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
In-Reply-To: <CAMabFbVjAHSG2TSCMnQUnmK9C0DHy89590ZWxpTwPetmZODULw@mail.gmail.com>
References: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
 <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>
 <CAE2FW2=YAvDEPkdJh6fp+ZjjiQmDFypUWgUDBDtSs=6LqOAscw@mail.gmail.com>
 <CAMabFbVjAHSG2TSCMnQUnmK9C0DHy89590ZWxpTwPetmZODULw@mail.gmail.com>
Message-ID: <CAE2FW2nDq=LdxYkeRLkLxm9NNOZ48CVUSm_QutzEq0rYaqXMsA@mail.gmail.com>

Thanks David. Those discussion boards are indeed very helpful.

Thanks for providing the lead.

Best,

Mike

On Mon, Apr 5, 2021 at 12:06 PM David Nicholson <nicholdav at gmail.com> wrote:

> You might find more people that can help with other libraries such as
> XGBoost and conda on stack overflow, a list dedicated to those tools, or
> their github repositories.
> https://discuss.xgboost.ai/
> https://groups.google.com/a/continuum.io/g/conda
>
> David Nicholson, Ph.D.
> https://nicholdav.info/
> https://github.com/NickleDave
> Prinz lab <http://www.biology.emory.edu/research/Prinz/>, Emory
> University, Atlanta, GA, USA
>
>
> On Mon, Apr 5, 2021 at 11:28 AM C W <tmrsg11 at gmail.com> wrote:
>
>> Update:
>>
>> It seems I've already installed XGBoost before. But, I get the following
>> error:
>>
>> >>> import xgboost
>> Traceback (most recent call last):
>>   File "<stdin>", line 1, in <module>
>>   File
>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/__init__.py",
>> line 9, in <module>
>>     from .core import DMatrix, DeviceQuantileDMatrix, Booster
>>   File
>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
>> line 174, in <module>
>>     _LIB = _load_lib()
>>   File
>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
>> line 157, in _load_lib
>>     raise XGBoostError(
>> xgboost.core.XGBoostError: XGBoost Library (libxgboost.dylib) could not
>> be loaded.
>> Likely causes:
>>   * OpenMP runtime is not installed (vcomp140.dll or libgomp-1.dll for
>> Windows, libomp.dylib for Mac OSX, libgomp.so for Linux and other UNIX-like
>> OSes). Mac OSX users: Run `brew install libomp` to install OpenMP runtime.
>>   * You are running 32-bit Python on a 64-bit OS
>> Error message(s):
>> ['dlopen(/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib,
>> 6): Library not loaded: /usr/local/opt/libomp/lib/libomp.dylib\n
>>  Referenced from:
>> /Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib\n
>>  Reason: image not found']
>>
>> It seems OpenMP runtime the one I am missing. I can install by running
>> > brew install libomp
>>
>> But, I don't have brew on this computer. Any work around?
>>
>> Thanks!
>>
>> On Mon, Apr 5, 2021 at 10:54 AM C W <tmrsg11 at gmail.com> wrote:
>>
>>> Hello again,
>>>
>>> I have 3 follow-up questions.
>>>
>>> 1) Upon searching, Anaconda website (
>>> https://anaconda.org/anaconda/py-xgboost) says that you can install
>>> with,
>>> > conda install -c anaconda py-xgboost
>>> I have miniconda, not anaconda, I guess I just replace it anaconda with
>>> minconda?
>>>
>>> 2) Using pip3 command,
>>> > pip3 install xgboost
>>> I don't have pip.
>>>
>>> 3) From XGBoost website, I now see that you can build XGBoost from
>>> source (https://xgboost.readthedocs.io/en/latest/build.html)
>>>
>>> Question: will all the 3 methods install XGBoost in the same folder?
>>>
>>> Thanks a lot!
>>>
>>> On Mon, Apr 5, 2021 at 10:35 AM C W <tmrsg11 at gmail.com> wrote:
>>>
>>>> Hello all,
>>>>
>>>> I can't install pip on this computer. It has conda installed (probably
>>>> not helpful). Is there a work around to install XGBoost and packages?
>>>>
>>>> I remember reading on stackoverflow, there were some simple commands to
>>>> do it. I actually used it to install packages without pip.
>>>>
>>>> I can't find the post anymore, could anyone help?
>>>>
>>>> Thanks so much!
>>>>
>>>> Mike
>>>>
>>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From sebas0 at gmail.com  Tue Apr  6 23:43:40 2021
From: sebas0 at gmail.com (Sebastian Gurovich)
Date: Wed, 7 Apr 2021 00:43:40 -0300
Subject: [scikit-learn] Can I install Python ML library such as XGBoost
 without pip?
In-Reply-To: <CAE2FW2nDq=LdxYkeRLkLxm9NNOZ48CVUSm_QutzEq0rYaqXMsA@mail.gmail.com>
References: <CAE2FW2nH6aGGKSQkz1JDiUb29Ccd60Lh+1A__QA9rsZvHOuvtQ@mail.gmail.com>
 <CAE2FW2k3whRX7ozaVEMSQ-rf1ottCm_UPwjx32sYE87Hk3KqcA@mail.gmail.com>
 <CAE2FW2=YAvDEPkdJh6fp+ZjjiQmDFypUWgUDBDtSs=6LqOAscw@mail.gmail.com>
 <CAMabFbVjAHSG2TSCMnQUnmK9C0DHy89590ZWxpTwPetmZODULw@mail.gmail.com>
 <CAE2FW2nDq=LdxYkeRLkLxm9NNOZ48CVUSm_QutzEq0rYaqXMsA@mail.gmail.com>
Message-ID: <CAPx0h+=MBssN0RAbmFuamDxGzdkfzpJCbKOeT-js+_AOSLJc5g@mail.gmail.com>

Could a Virtual Machine be an option for you?

Good luck

On Tue, 6 Apr 2021, 7:00 pm C W, <tmrsg11 at gmail.com> wrote:

> Thanks David. Those discussion boards are indeed very helpful.
>
> Thanks for providing the lead.
>
> Best,
>
> Mike
>
> On Mon, Apr 5, 2021 at 12:06 PM David Nicholson <nicholdav at gmail.com>
> wrote:
>
>> You might find more people that can help with other libraries such as
>> XGBoost and conda on stack overflow, a list dedicated to those tools, or
>> their github repositories.
>> https://discuss.xgboost.ai/
>> https://groups.google.com/a/continuum.io/g/conda
>>
>> David Nicholson, Ph.D.
>> https://nicholdav.info/
>> https://github.com/NickleDave
>> Prinz lab <http://www.biology.emory.edu/research/Prinz/>, Emory
>> University, Atlanta, GA, USA
>>
>>
>> On Mon, Apr 5, 2021 at 11:28 AM C W <tmrsg11 at gmail.com> wrote:
>>
>>> Update:
>>>
>>> It seems I've already installed XGBoost before. But, I get the following
>>> error:
>>>
>>> >>> import xgboost
>>> Traceback (most recent call last):
>>>   File "<stdin>", line 1, in <module>
>>>   File
>>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/__init__.py",
>>> line 9, in <module>
>>>     from .core import DMatrix, DeviceQuantileDMatrix, Booster
>>>   File
>>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
>>> line 174, in <module>
>>>     _LIB = _load_lib()
>>>   File
>>> "/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/core.py",
>>> line 157, in _load_lib
>>>     raise XGBoostError(
>>> xgboost.core.XGBoostError: XGBoost Library (libxgboost.dylib) could not
>>> be loaded.
>>> Likely causes:
>>>   * OpenMP runtime is not installed (vcomp140.dll or libgomp-1.dll for
>>> Windows, libomp.dylib for Mac OSX, libgomp.so for Linux and other UNIX-like
>>> OSes). Mac OSX users: Run `brew install libomp` to install OpenMP runtime.
>>>   * You are running 32-bit Python on a 64-bit OS
>>> Error message(s):
>>> ['dlopen(/Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib,
>>> 6): Library not loaded: /usr/local/opt/libomp/lib/libomp.dylib\n
>>>  Referenced from:
>>> /Users/mike/opt/miniconda3/lib/python3.8/site-packages/xgboost/lib/libxgboost.dylib\n
>>>  Reason: image not found']
>>>
>>> It seems OpenMP runtime the one I am missing. I can install by running
>>> > brew install libomp
>>>
>>> But, I don't have brew on this computer. Any work around?
>>>
>>> Thanks!
>>>
>>> On Mon, Apr 5, 2021 at 10:54 AM C W <tmrsg11 at gmail.com> wrote:
>>>
>>>> Hello again,
>>>>
>>>> I have 3 follow-up questions.
>>>>
>>>> 1) Upon searching, Anaconda website (
>>>> https://anaconda.org/anaconda/py-xgboost) says that you can install
>>>> with,
>>>> > conda install -c anaconda py-xgboost
>>>> I have miniconda, not anaconda, I guess I just replace it anaconda with
>>>> minconda?
>>>>
>>>> 2) Using pip3 command,
>>>> > pip3 install xgboost
>>>> I don't have pip.
>>>>
>>>> 3) From XGBoost website, I now see that you can build XGBoost from
>>>> source (https://xgboost.readthedocs.io/en/latest/build.html)
>>>>
>>>> Question: will all the 3 methods install XGBoost in the same folder?
>>>>
>>>> Thanks a lot!
>>>>
>>>> On Mon, Apr 5, 2021 at 10:35 AM C W <tmrsg11 at gmail.com> wrote:
>>>>
>>>>> Hello all,
>>>>>
>>>>> I can't install pip on this computer. It has conda installed (probably
>>>>> not helpful). Is there a work around to install XGBoost and packages?
>>>>>
>>>>> I remember reading on stackoverflow, there were some simple commands
>>>>> to do it. I actually used it to install packages without pip.
>>>>>
>>>>> I can't find the post anymore, could anyone help?
>>>>>
>>>>> Thanks so much!
>>>>>
>>>>> Mike
>>>>>
>>>> _______________________________________________
>>> scikit-learn mailing list
>>> scikit-learn at python.org
>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From myabakhova at gmail.com  Wed Apr 14 16:06:36 2021
From: myabakhova at gmail.com (Maiia Bakhova)
Date: Wed, 14 Apr 2021 13:06:36 -0700
Subject: [scikit-learn] Elbow method module for estimating of optimal
 clustering
Message-ID: <CAC7JaAoLZ-xRdFJKcC0bCWWxQjO4Dp6c8MmqNh4UWTqULNU2Wg@mail.gmail.com>

Hello,
A while ago I made a numeric computation of Elbow method to estimate an
optimal number of clusters created by K-means and presented it in
scikit-learn digest as a function. As a result
I got a lot of clones from my github repo, and was encouraged to work
further on it. I got
feedback from people with whom I discussed it. Now it is in the format of
scikit-learn Estimator
and has bootstrapping to verify if the chosen number is more or less
reliable and not too random.
It returns a suggested optimal number and a dictionary of all calculated
suggestions with corresponding frequencies.
Here is the method:
https://github.com/Mathemilda/Numeric_ElbowMethod_For_K-means/blob/master/EstimatedClusterNumberWithWCSS.py
Here is an example of its application in a jupiter notebook:
https://github.com/Mathemilda/Numeric_ElbowMethod_For_K-means/blob/master/A%20scikit-learn%20compatible%20method%20with%20WCSS%20metric.ipynb
I got a number of other suggestions, like incorporating other metrics and
methods.
I have seen a discussion about it with some pullrequests on scikit-learn
github, but it does not appear to be finished. As I understand a lot people
would like to have something now,
so I offer my work.
Please do not hesitate with questions or suggestions,
Mya

-- 
Maiia Bakhova
Mathematician in Data Science
http://myabakhova.blogspot.com
https://www.linkedin.com/in/myabakhova
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From timothee.mathieu at universite-paris-saclay.fr  Wed Apr 14 15:33:26 2021
From: timothee.mathieu at universite-paris-saclay.fr (Timothee Mathieu)
Date: Wed, 14 Apr 2021 21:33:26 +0200 (CEST)
Subject: [scikit-learn] ANN: scikit-learn-extra 0.2.0 released
In-Reply-To: <1551328408.4203535.1618426036190.JavaMail.zimbra@universite-paris-saclay.fr>
References: <1551328408.4203535.1618426036190.JavaMail.zimbra@universite-paris-saclay.fr>
Message-ID: <2088640604.4218987.1618428806889.JavaMail.zimbra@universite-paris-saclay.fr>

Hello,

We're happy to announce the 0.2.0 version of scikit-learn-extra.
scikit-learn-extra is a Python module for machine learning that extends scikit-learn. 
It includes algorithms that are useful but do not satisfy the scikit-learn inclusion criteria. 
This new release includes in particular new clustering and robust algorithms.

This release should be fully compatible with scikit-learn 0.23
The full changelog can be found here: [ https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-0-2-0 | https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-0-2-0 ] The new release of scikit-learn-extra is available via pip and conda.
For more information, please visit the documentation: [ https://scikit-learn-extra.readthedocs.io/en/stable/ | https://scikit-learn-extra.readthedocs.io/en/stable/ ] Best regards,
Timoth?e, on behalf of the scikit-learn-extra team. 

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From g.lemaitre58 at gmail.com  Thu Apr 15 04:59:22 2021
From: g.lemaitre58 at gmail.com (=?UTF-8?Q?Guillaume_Lema=C3=AEtre?=)
Date: Thu, 15 Apr 2021 10:59:22 +0200
Subject: [scikit-learn] ANN: scikit-learn-extra 0.2.0 released
In-Reply-To: <2088640604.4218987.1618428806889.JavaMail.zimbra@universite-paris-saclay.fr>
References: <1551328408.4203535.1618426036190.JavaMail.zimbra@universite-paris-saclay.fr>
 <2088640604.4218987.1618428806889.JavaMail.zimbra@universite-paris-saclay.fr>
Message-ID: <CACDxx9h8wX6Z_ezxDg-SO_OWXweFLAgxjN3KEA36kZiasGGCFQ@mail.gmail.com>

Cool work guys. Thanks to the team that takes care about these extensions.

On Wed, 14 Apr 2021 at 22:54, Timothee Mathieu <
timothee.mathieu at universite-paris-saclay.fr> wrote:

> Hello,
>
> We're happy to announce the 0.2.0 version of scikit-learn-extra.
> scikit-learn-extra is a Python module for machine learning that extends scikit-learn.
> It includes algorithms that are useful but do not satisfy the scikit-learn inclusion criteria.
> This new release includes in particular new clustering and robust algorithms.
>
> This release should be fully compatible with scikit-learn 0.23
> The full changelog can be found here: https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-0-2-0
>
> The new release of scikit-learn-extra is available via pip and conda.
> For more information, please visit the documentation: https://scikit-learn-extra.readthedocs.io/en/stable/
>
> Best regards,
> Timoth?e, on behalf of the scikit-learn-extra team.
>
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>


-- 
Guillaume Lemaitre
Scikit-learn @ Inria Foundation
https://glemaitre.github.io/
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From mujjub1997 at gmail.com  Fri Apr 16 08:36:52 2021
From: mujjub1997 at gmail.com (Mujeebur Rahman)
Date: Fri, 16 Apr 2021 18:06:52 +0530
Subject: [scikit-learn] GridSearchCV not working properly
Message-ID: <CAPuO0C+=Vr0CGN7q8m3K90yXvm1EaCxaue6tSA_n8HhmWtWN5Q@mail.gmail.com>

Dear Team,

I really like to work with sklearn tools. But I've been facing issues ever
since the latest version was released. It is about the GridSearchCV
function of model_selection.

With the previous version, I ran GradientBoostingClassifier with a set of
hyperparameters and fed it to GridSearchCV, setting verbose to 5. The train
data had around 800 rows and 100 columns. The model completed running
within 2-3 minutes.

With the latest version, I ran the same code without any changes. The only
change is with the number of rows, where around 200 rows have been added
extra. This time wheb I ran the code, it took nearly 20 minutes to
complete. And the verbose steps also didn't show up.

Please fix this issue as soon as possible. I really look forward to hearing
from you.

Thanks and Regards,
Mujeebur Rahman
Data Analyst
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From g.lemaitre58 at gmail.com  Fri Apr 16 08:57:06 2021
From: g.lemaitre58 at gmail.com (=?UTF-8?Q?Guillaume_Lema=C3=AEtre?=)
Date: Fri, 16 Apr 2021 14:57:06 +0200
Subject: [scikit-learn] GridSearchCV not working properly
In-Reply-To: <CAPuO0C+=Vr0CGN7q8m3K90yXvm1EaCxaue6tSA_n8HhmWtWN5Q@mail.gmail.com>
References: <CAPuO0C+=Vr0CGN7q8m3K90yXvm1EaCxaue6tSA_n8HhmWtWN5Q@mail.gmail.com>
Message-ID: <CACDxx9g-zvVpmLV2ckg4FaM9uSBuJXq1hfRUb2arp-hzNZLgeg@mail.gmail.com>

Hi Mujeebur,

On the top of the head, I don't recall any drastic changes in
GradientBoostingClassifier and GridSearchCV in the last version.
We start to continuously benchmark performance regressions and we did not
notice anything but it is possible that we missed it (or we do not test
with the sort of data that you have).

Please open an issue in GitHub with a reproducible minimal example and give
information regarding your platform and environment such that we can try to
reproduce:
https://github.com/scikit-learn/scikit-learn/issues

> Please fix this issue as soon as possible.

I would personally appreciate it if you could drop this type of statement
in your next post.

On Fri, 16 Apr 2021 at 14:38, Mujeebur Rahman <mujjub1997 at gmail.com> wrote:

> Dear Team,
>
> I really like to work with sklearn tools. But I've been facing issues ever
> since the latest version was released. It is about the GridSearchCV
> function of model_selection.
>
> With the previous version, I ran GradientBoostingClassifier with a set of
> hyperparameters and fed it to GridSearchCV, setting verbose to 5. The train
> data had around 800 rows and 100 columns. The model completed running
> within 2-3 minutes.
>
> With the latest version, I ran the same code without any changes. The only
> change is with the number of rows, where around 200 rows have been added
> extra. This time wheb I ran the code, it took nearly 20 minutes to
> complete. And the verbose steps also didn't show up.
>
> Please fix this issue as soon as possible. I really look forward to
> hearing from you.
>
> Thanks and Regards,
> Mujeebur Rahman
> Data Analyst
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>


-- 
Guillaume Lemaitre
Scikit-learn @ Inria Foundation
https://glemaitre.github.io/
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From reshama.stat at gmail.com  Fri Apr 16 10:25:01 2021
From: reshama.stat at gmail.com (Reshama Shaikh)
Date: Fri, 16 Apr 2021 10:25:01 -0400
Subject: [scikit-learn] Open Source: sustainability and etiquette
Message-ID: <CAKPCsujRtuY4XN3ck87C7-RKJQHvQuWTy8Fwj_bT+3wMNL9Z4A@mail.gmail.com>

Hello,
I've seen some excellent resources that have explained open source, its
sustainability, challenges and *indirectly, the etiquette*.

I am starting to compile the list here [a].

This keynote by Stuart Geiger is a must-watch:  The Invisible Work of
Maintaining & Sustaining Open Source Software   [b]

There is one more video by Emily someone who was at Microsoft, but is now a
professor somewhere, and I am trying to track that video down.  I think
it's from 2017.  I'll add it to the list once I find it.  If anyone knows
the full name of the speaker, please share.

[a]
https://www.dataumbrella.org/open-source/open-source-sustainability

[b]
https://www.youtube.com/watch?v=PM3iltcaIL8

Best,
Reshama
---
Reshama Shaikh
she/her
Blog <https://reshamas.github.io> | Twitter <https://twitter.com/reshamas>
| LinkedIn <https://www.linkedin.com/in/reshamas/> | GitHub
<https://github.com/reshamas>

Data Umbrella <https://www.dataumbrella.org>
NYC PyLadies
<https://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTt6zEs68RbcMfjPcajNHTKtn9NmwqQbJhe15mAZ1gz2La_s50GiGgQPBz9c9AKCDbbu2LRERFOLQHDZ3rAVGAkUEIFdmeKWgLQ1JD-2FBfVxXpI86J1oyur7RYRzToaqco1fWUx-2FWPOn-2FLCyCICxwu5bjlHJvtSvVekt71L43UiQL8dMjr0HfGP-2FSeiGQFG0QQxzS-2FX5o4Q8Ch-2BHrlA5hsa9VyPXC5FvBn1cNbkmil3SgwH7HWFmXsKFJ7RYrzZR0EwWFIMarRA8-2BTgd8yXJYlfxogk-3D>
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From joel.nothman at gmail.com  Sat Apr 17 06:33:21 2021
From: joel.nothman at gmail.com (Joel Nothman)
Date: Sat, 17 Apr 2021 20:33:21 +1000
Subject: [scikit-learn] ANN: scikit-learn-extra 0.2.0 released
In-Reply-To: <CACDxx9h8wX6Z_ezxDg-SO_OWXweFLAgxjN3KEA36kZiasGGCFQ@mail.gmail.com>
References: <1551328408.4203535.1618426036190.JavaMail.zimbra@universite-paris-saclay.fr>
 <2088640604.4218987.1618428806889.JavaMail.zimbra@universite-paris-saclay.fr>
 <CACDxx9h8wX6Z_ezxDg-SO_OWXweFLAgxjN3KEA36kZiasGGCFQ@mail.gmail.com>
Message-ID: <CAAkaFLUsrEnQKNXoQVFuk1VSj75sHcvWsPw=Rf7gySP2eJM3_w@mail.gmail.com>

Agreed. Well done on making Extra happen!

On Thu, 15 Apr 2021, 7:00 pm Guillaume Lema?tre, <g.lemaitre58 at gmail.com>
wrote:

> Cool work guys. Thanks to the team that takes care about these extensions.
>
> On Wed, 14 Apr 2021 at 22:54, Timothee Mathieu <
> timothee.mathieu at universite-paris-saclay.fr> wrote:
>
>> Hello,
>>
>> We're happy to announce the 0.2.0 version of scikit-learn-extra.
>> scikit-learn-extra is a Python module for machine learning that extends scikit-learn.
>> It includes algorithms that are useful but do not satisfy the scikit-learn inclusion criteria.
>> This new release includes in particular new clustering and robust algorithms.
>>
>> This release should be fully compatible with scikit-learn 0.23
>> The full changelog can be found here: https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-0-2-0
>>
>> The new release of scikit-learn-extra is available via pip and conda.
>> For more information, please visit the documentation: https://scikit-learn-extra.readthedocs.io/en/stable/
>>
>> Best regards,
>> Timoth?e, on behalf of the scikit-learn-extra team.
>>
>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>
>
> --
> Guillaume Lemaitre
> Scikit-learn @ Inria Foundation
> https://glemaitre.github.io/
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From adrin.jalali at gmail.com  Mon Apr 19 09:25:09 2021
From: adrin.jalali at gmail.com (Adrin)
Date: Mon, 19 Apr 2021 15:25:09 +0200
Subject: [scikit-learn] Open Source: sustainability and etiquette
In-Reply-To: <CAKPCsujRtuY4XN3ck87C7-RKJQHvQuWTy8Fwj_bT+3wMNL9Z4A@mail.gmail.com>
References: <CAKPCsujRtuY4XN3ck87C7-RKJQHvQuWTy8Fwj_bT+3wMNL9Z4A@mail.gmail.com>
Message-ID: <CAEOrW4-fk1Vz5EN7MgCyU8kH1-tGV18STfcb6p7D28sRyyqxPg@mail.gmail.com>

This is a really good initiative Reshama, thanks for sharing.

Have you seen CHAOSScon talks and activities? They're really good, and
touch on a lot of really good stuff when it comes to open source
communities and sustainability.
Eg.:  https://chaoss.community/chaosscon-2020-eu/

Cheers,
Adrin

On Fri, Apr 16, 2021 at 4:26 PM Reshama Shaikh <reshama.stat at gmail.com>
wrote:

> Hello,
> I've seen some excellent resources that have explained open source, its
> sustainability, challenges and *indirectly, the etiquette*.
>
> I am starting to compile the list here [a].
>
> This keynote by Stuart Geiger is a must-watch:  The Invisible Work of
> Maintaining & Sustaining Open Source Software   [b]
>
> There is one more video by Emily someone who was at Microsoft, but is now
> a professor somewhere, and I am trying to track that video down.  I think
> it's from 2017.  I'll add it to the list once I find it.  If anyone knows
> the full name of the speaker, please share.
>
> [a]
> https://www.dataumbrella.org/open-source/open-source-sustainability
>
> [b]
> https://www.youtube.com/watch?v=PM3iltcaIL8
>
> Best,
> Reshama
> ---
> Reshama Shaikh
> she/her
> Blog <https://reshamas.github.io> | Twitter <https://twitter.com/reshamas>
> | LinkedIn <https://www.linkedin.com/in/reshamas/> | GitHub
> <https://github.com/reshamas>
>
> Data Umbrella <https://www.dataumbrella.org>
> NYC PyLadies
> <https://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTt6zEs68RbcMfjPcajNHTKtn9NmwqQbJhe15mAZ1gz2La_s50GiGgQPBz9c9AKCDbbu2LRERFOLQHDZ3rAVGAkUEIFdmeKWgLQ1JD-2FBfVxXpI86J1oyur7RYRzToaqco1fWUx-2FWPOn-2FLCyCICxwu5bjlHJvtSvVekt71L43UiQL8dMjr0HfGP-2FSeiGQFG0QQxzS-2FX5o4Q8Ch-2BHrlA5hsa9VyPXC5FvBn1cNbkmil3SgwH7HWFmXsKFJ7RYrzZR0EwWFIMarRA8-2BTgd8yXJYlfxogk-3D>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From bsipocz at gmail.com  Mon Apr 19 18:48:41 2021
From: bsipocz at gmail.com (Brigitta Sipocz)
Date: Mon, 19 Apr 2021 15:48:41 -0700
Subject: [scikit-learn] Open Source: sustainability and etiquette
In-Reply-To: <CAEOrW4-fk1Vz5EN7MgCyU8kH1-tGV18STfcb6p7D28sRyyqxPg@mail.gmail.com>
References: <CAKPCsujRtuY4XN3ck87C7-RKJQHvQuWTy8Fwj_bT+3wMNL9Z4A@mail.gmail.com>
 <CAEOrW4-fk1Vz5EN7MgCyU8kH1-tGV18STfcb6p7D28sRyyqxPg@mail.gmail.com>
Message-ID: <CAEjJ3fiyzScwSbw4hBc8aOExC5A3ZW7_yr2fo_=x6dJnCsgAgg@mail.gmail.com>

Hi,

I've also very much liked Nadia Eghbal's book: Working in public; The
making and maintenance of open source software. I haven't yet attended a
conference where she was a speaker, but I'm certain there are some relevant
recordings on youtube.

Cheers,
 Brigitta


On Mon, 19 Apr 2021 at 06:27, Adrin <adrin.jalali at gmail.com> wrote:

> This is a really good initiative Reshama, thanks for sharing.
>
> Have you seen CHAOSScon talks and activities? They're really good, and
> touch on a lot of really good stuff when it comes to open source
> communities and sustainability.
> Eg.:  https://chaoss.community/chaosscon-2020-eu/
>
> Cheers,
> Adrin
>
> On Fri, Apr 16, 2021 at 4:26 PM Reshama Shaikh <reshama.stat at gmail.com>
> wrote:
>
>> Hello,
>> I've seen some excellent resources that have explained open source, its
>> sustainability, challenges and *indirectly, the etiquette*.
>>
>> I am starting to compile the list here [a].
>>
>> This keynote by Stuart Geiger is a must-watch:  The Invisible Work of
>> Maintaining & Sustaining Open Source Software   [b]
>>
>> There is one more video by Emily someone who was at Microsoft, but is now
>> a professor somewhere, and I am trying to track that video down.  I think
>> it's from 2017.  I'll add it to the list once I find it.  If anyone knows
>> the full name of the speaker, please share.
>>
>> [a]
>> https://www.dataumbrella.org/open-source/open-source-sustainability
>>
>> [b]
>> https://www.youtube.com/watch?v=PM3iltcaIL8
>>
>> Best,
>> Reshama
>> ---
>> Reshama Shaikh
>> she/her
>> Blog <https://reshamas.github.io> | Twitter
>> <https://twitter.com/reshamas> | LinkedIn
>> <https://www.linkedin.com/in/reshamas/> | GitHub
>> <https://github.com/reshamas>
>>
>> Data Umbrella <https://www.dataumbrella.org>
>> NYC PyLadies
>> <https://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTt6zEs68RbcMfjPcajNHTKtn9NmwqQbJhe15mAZ1gz2La_s50GiGgQPBz9c9AKCDbbu2LRERFOLQHDZ3rAVGAkUEIFdmeKWgLQ1JD-2FBfVxXpI86J1oyur7RYRzToaqco1fWUx-2FWPOn-2FLCyCICxwu5bjlHJvtSvVekt71L43UiQL8dMjr0HfGP-2FSeiGQFG0QQxzS-2FX5o4Q8Ch-2BHrlA5hsa9VyPXC5FvBn1cNbkmil3SgwH7HWFmXsKFJ7RYrzZR0EwWFIMarRA8-2BTgd8yXJYlfxogk-3D>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From marmochiaskl at gmail.com  Wed Apr 21 06:03:57 2021
From: marmochiaskl at gmail.com (Chiara Marmo)
Date: Wed, 21 Apr 2021 12:03:57 +0200
Subject: [scikit-learn] Monthly meeting April 26th 2021
Message-ID: <CAGfF14_0L_bpcH64YJei7H_DGR+oL3BV-b-7-=PN65Wh7g5xyw@mail.gmail.com>

Dear list,

The scikit-learn monthly meeting will take place on Monday April 26th at
1PM UTC:
<https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=01&day=04&hour=20&min=0&sec=0&p1=179&p2=240&p3=195&p4=224>
<https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=01&day=25&hour=20&min=0&sec=0&p1=179&p2=240&p3=195&p4=224>
https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=4&day=26&hour=13&min=0&sec=0&p1=195&p2=224&p3=179&p4=136&p5=240
<https://www.google.com/url?q=https://www.timeanddate.com/worldclock/meetingtime.html?month%3D10%26day%3D26%26year%3D2020%26p1%3D179%26p2%3D240%26p3%3D195%26p4%3D224%26iv%3D0&sa=D&source=calendar&usd=2&usg=AOvVaw1nSuFYBdv9nvJzi_QftPp->
<https://www.google.com/url?q=https://www.timeanddate.com/worldclock/meetingtime.html?month%3D10%26day%3D26%26year%3D2020%26p1%3D179%26p2%3D240%26p3%3D195%26p4%3D224%26iv%3D0&sa=D&source=calendar&usd=2&usg=AOvVaw1nSuFYBdv9nvJzi_QftPp->

While these meetings are mainly for core-devs to discuss the current
topics, non core-devs and other project maintainers are welcome.

Feel free to join, using the following link:

https://meet.google.com/xhq-yoga-rtf

If you plan to attend and you would like to discuss something specific
about your contribution please add your name (or github pseudo) in the "
Contributors <https://hackmd.io/k4gBAPkZR-GpQSOd80pFpQ#Contributors>"
section, of the public pad:

<https://hackmd.io/qtKt7pTNSXanU-MJOIMxbw>
https://hackmd.io/k4gBAPkZR-GpQSOd80pFpQ

Best

Chiara
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From matt.schoenbauer3 at gmail.com  Thu Apr 22 12:37:26 2021
From: matt.schoenbauer3 at gmail.com (Matt Schoenbauer)
Date: Thu, 22 Apr 2021 12:37:26 -0400
Subject: [scikit-learn] Efficient forward stepwise regression
Message-ID: <CAD4rvHtAchbN7jcKa2ZKx3G_m1+2XXp1_LPsaf=UNY=5ORyQzw@mail.gmail.com>

Hello sklearn developers,

I'd like to implement a forward stepwise regression algorithm using the
efficient procedure described in the first problem here
<http://stat.rutgers.edu/home/hxiao/stat588_2011/hw1.pdf>. It does not seem
that such a model exists anywhere in Python. Would it be useful for me to
write this model up for sklearn?

If you're interested, here's a high-level view of how I think it would work:

- The model would have sklearn.linear_model.LinearRegression as its base
class.
- The additional model parameters would include

   - An array of the indices (or column names) of the features in X1
   - The Q and R matrices

- The additional methods would include

   - An add_features() method that adds a specified number of features to
   the model. Updates all model parameters
   - A fit() method that requires a specification of the number of
   parameters to fit and optional sample weight. It calls the add_features
   method once on a model with no features.

I would do this for OLS first, but supposedly it could be adapted for
regularized models as well.

How does this sound?

Thanks,

Matt S.
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From alexandre.gramfort at inria.fr  Mon Apr 26 02:23:03 2021
From: alexandre.gramfort at inria.fr (Alexandre Gramfort)
Date: Mon, 26 Apr 2021 08:23:03 +0200
Subject: [scikit-learn] Efficient forward stepwise regression
In-Reply-To: <CAD4rvHtAchbN7jcKa2ZKx3G_m1+2XXp1_LPsaf=UNY=5ORyQzw@mail.gmail.com>
References: <CAD4rvHtAchbN7jcKa2ZKx3G_m1+2XXp1_LPsaf=UNY=5ORyQzw@mail.gmail.com>
Message-ID: <CADeotZpkZy_aCHK7rCjyN7jZpP8BtBJZ8E+46reVT9SquiVzmg@mail.gmail.com>

hi Matt,

I'd like to implement a forward stepwise regression algorithm using the
> efficient procedure described in the first problem here
> <http://stat.rutgers.edu/home/hxiao/stat588_2011/hw1.pdf>. It does not
> seem that such a model exists anywhere in Python. Would it be useful for me
> to write this model up for sklearn?
>

to be considered I would first ask you to evaluate and discuss what you
think it will bring
over existing estimators. Typically do you foresee a clear benefit compared
to Lars or LassoLars ?

For more see
https://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms


> If you're interested, here's a high-level view of how I think it would
> work:
>
> - The model would have sklearn.linear_model.LinearRegression as its base
> class.
> - The additional model parameters would include
>
>    - An array of the indices (or column names) of the features in X1
>    - The Q and R matrices
>
> - The additional methods would include
>
>    - An add_features() method that adds a specified number of features to
>    the model. Updates all model parameters
>    - A fit() method that requires a specification of the number of
>    parameters to fit and optional sample weight. It calls the add_features
>    method once on a model with no features.
>
>
the API of scikit-learn estimator is quite strict. See

https://scikit-learn.org/stable/developers/develop.html?highlight=check_estimator

I invite you to read
https://scikit-learn.org/stable/developers/contributing.html?highlight=contribut
if you are willing to help the team.

Alex


> I would do this for OLS first, but supposedly it could be adapted for
> regularized models as well.
>
> How does this sound?
>
> Thanks,
>
> Matt S.
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From betsey_gogo at comcast.net  Mon Apr 26 17:37:50 2021
From: betsey_gogo at comcast.net (betsey_gogo)
Date: Mon, 26 Apr 2021 15:37:50 -0600
Subject: [scikit-learn] scikit problems
Message-ID: <01c901d73ae4$6b671070$42353150$@comcast.net>

I am getting frustrated. I am unable to run any scikit learning code because
of an OS error

 

OSError: [WinError 193] %1 is not a valid Win32 application

 

I have tried 64 bit and 32 bit Anaconda installations to no avail.

I have searched for help on the web. Others have seen this issue but the
solutions are at best unclear.

I don't know if I have an incorrect path variable of something more serious.

 

Would you help?

 

Orest Gogosha  "GOGO"

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From christophe at pallier.org  Mon Apr 26 18:03:14 2021
From: christophe at pallier.org (Christophe Pallier)
Date: Tue, 27 Apr 2021 00:03:14 +0200
Subject: [scikit-learn] scikit problems
In-Reply-To: <01c901d73ae4$6b671070$42353150$@comcast.net>
References: <01c901d73ae4$6b671070$42353150$@comcast.net>
Message-ID: <CALyk9bzguJytjGDWdtXhF-VvNa2Uaud4h3ugioz4wJkhEcMYQQ@mail.gmail.com>

Can you provide the precise command you typed and the *entire* error
message (including the python line that caused the issue)?

On Mon, 26 Apr 2021, 23:41 betsey_gogo, <betsey_gogo at comcast.net> wrote:

> I am getting frustrated. I am unable to run any scikit learning code
> because of an OS error
>
>
>
> *OSError*: [WinError 193] %1 is not a valid Win32 application
>
>
>
> I have tried 64 bit and 32 bit Anaconda installations to no avail.
>
> I have searched for help on the web. Others have seen this issue but the
> solutions are at best unclear.
>
> I don?t know if I have an incorrect path variable of something more
> serious.
>
>
>
> Would you help?
>
>
>
> Orest Gogosha  ?GOGO?
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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From christophe at pallier.org  Mon Apr 26 18:15:37 2021
From: christophe at pallier.org (Christophe Pallier)
Date: Tue, 27 Apr 2021 00:15:37 +0200
Subject: [scikit-learn] scikit problems
In-Reply-To: <CALyk9bzguJytjGDWdtXhF-VvNa2Uaud4h3ugioz4wJkhEcMYQQ@mail.gmail.com>
References: <01c901d73ae4$6b671070$42353150$@comcast.net>
 <CALyk9bzguJytjGDWdtXhF-VvNa2Uaud4h3ugioz4wJkhEcMYQQ@mail.gmail.com>
Message-ID: <CALyk9byEjazpuV0F60BGUPsy5W5dJzOQ+gMwOdH6kLUqz70c4w@mail.gmail.com>

I have just googled the issue and it is not specific to sklearn.
It seems to be due to a messed-up python installation. People fixed the
problem by deleting the folder containing the problematic module(s), or
even resinstalled anaconda python (some had mixed up 32 bits libs with
64bit python).


On Tue, 27 Apr 2021, 00:03 Christophe Pallier, <christophe at pallier.org>
wrote:

> Can you provide the precise command you typed and the *entire* error
> message (including the python line that caused the issue)?
>
> On Mon, 26 Apr 2021, 23:41 betsey_gogo, <betsey_gogo at comcast.net> wrote:
>
>> I am getting frustrated. I am unable to run any scikit learning code
>> because of an OS error
>>
>>
>>
>> *OSError*: [WinError 193] %1 is not a valid Win32 application
>>
>>
>>
>> I have tried 64 bit and 32 bit Anaconda installations to no avail.
>>
>> I have searched for help on the web. Others have seen this issue but the
>> solutions are at best unclear.
>>
>> I don?t know if I have an incorrect path variable of something more
>> serious.
>>
>>
>>
>> Would you help?
>>
>>
>>
>> Orest Gogosha  ?GOGO?
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn at python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>
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From g.lemaitre58 at gmail.com  Wed Apr 28 13:23:43 2021
From: g.lemaitre58 at gmail.com (=?UTF-8?Q?Guillaume_Lema=C3=AEtre?=)
Date: Wed, 28 Apr 2021 19:23:43 +0200
Subject: [scikit-learn] [ANN] scikit-learn 0.24.2 is online!
Message-ID: <CACDxx9gVLrxaPmcLjgcZj0cSHS_qdedA0n2+VvY53AhCrBFdzg@mail.gmail.com>

scikit-learn 0.24.2 is out on pypi.org and conda-forge!

This is a small maintenance release that fixes a couple of regressions:

https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then
install using:

conda install -c conda-forge scikit-learn


Thanks again to all the contributors and let's work towards version 1.0!
On behalf of the scikit-learn maintainer team.
-- 
Guillaume Lemaitre
Scikit-learn @ Inria Foundation
https://glemaitre.github.io/
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From rth.yurchak at gmail.com  Wed Apr 28 16:01:07 2021
From: rth.yurchak at gmail.com (Roman Yurchak)
Date: Wed, 28 Apr 2021 22:01:07 +0200
Subject: [scikit-learn] [ANN] scikit-learn 0.24.2 is online!
In-Reply-To: <CACDxx9gVLrxaPmcLjgcZj0cSHS_qdedA0n2+VvY53AhCrBFdzg@mail.gmail.com>
References: <CACDxx9gVLrxaPmcLjgcZj0cSHS_qdedA0n2+VvY53AhCrBFdzg@mail.gmail.com>
Message-ID: <11a54c2e-cd18-2c84-e8ad-41df8282fbdc@gmail.com>

Thanks for making this bug fix release happen!

-- 
Roman

On 28/04/2021 19:23, Guillaume Lema?tre wrote:
> scikit-learn 0.24.2 is out on pypi.org <http://pypi.org> and conda-forge!
> 
> This is a small maintenance release that fixes a couple of regressions:
> 
> https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2 
> <https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2>
> 
> You can upgrade with pip as usual:
> 
> |pip install -U scikit-learn |
> 
> The conda-forge builds will be available shortly, which you can then 
> install using:
> 
> |conda install -c conda-forge scikit-learn |
> 
> 
> Thanks again to all the contributors and let's work towards version 1.0!
> On behalf of the scikit-learn maintainer team.
> -- 
> Guillaume Lemaitre
> Scikit-learn @ Inria Foundation
> https://glemaitre.github.io/ <https://glemaitre.github.io/>
> 
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
> 

From betsey_gogo at comcast.net  Wed Apr 28 22:16:08 2021
From: betsey_gogo at comcast.net (betsey_gogo)
Date: Wed, 28 Apr 2021 20:16:08 -0600
Subject: [scikit-learn] scikit-learn Digest, Vol 61, Issue 12
In-Reply-To: <mailman.35.1619539209.17228.scikit-learn@python.org>
References: <mailman.35.1619539209.17228.scikit-learn@python.org>
Message-ID: <009f01d73c9d$9e5bb020$db131060$@comcast.net>

INPUT

 

import seaborn as sns

iris = sns.load_dataset('iris')

 

OUTPUT

 

OSError                                   Traceback (most recent call last)

<ipython-input-1-842ca3e1f505> in <module>

----> 1 import seaborn as sns

      2 iris = sns.load_dataset('iris')

 

D:\Anaconda\lib\site-packages\seaborn\__init__.py in <module>

      1 # Import seaborn objects

----> 2 from .rcmod import *  # noqa: F401,F403

      3 from .utils import *  # noqa: F401,F403

      4 from .palettes import *  # noqa: F401,F403

      5 from .relational import *  # noqa: F401,F403

 

D:\Anaconda\lib\site-packages\seaborn\rcmod.py in <module>

      3 import functools

      4 from distutils.version import LooseVersion

----> 5 import matplotlib as mpl

      6 from cycler import cycler

      7 from . import palettes

 

~\AppData\Roaming\Python\Python38\site-packages\matplotlib\__init__.py in
<module>

    136 # cbook must import matplotlib only within function

    137 # definitions, so it is safe to import from it here.

--> 138 from . import cbook, rcsetup

    139 from matplotlib.cbook import (

    140     MatplotlibDeprecationWarning, dedent, get_label,
sanitize_sequence)

 

~\AppData\Roaming\Python\Python38\site-packages\matplotlib\cbook\__init__.py
in <module>

     30 from weakref import WeakMethod

     31 

---> 32 import numpy as np

     33 

     34 import matplotlib

 

~\AppData\Roaming\Python\Python38\site-packages\numpy\__init__.py in
<module>

    138 

    139     # Allow distributors to run custom init code

--> 140     from . import _distributor_init

    141 

    142     from . import core

 

~\AppData\Roaming\Python\Python38\site-packages\numpy\_distributor_init.py
in <module>

     24                 # NOTE: would it change behavior to load ALL

     25                 # DLLs at this path vs. the name restriction?

---> 26                 WinDLL(os.path.abspath(filename))

     27                 DLL_filenames.append(filename)

     28     if len(DLL_filenames) > 1:

 

D:\Anaconda\lib\ctypes\__init__.py in __init__(self, name, mode, handle,
use_errno, use_last_error, winmode)

    379 

    380         if handle is None:

--> 381             self._handle = _dlopen(self._name, mode)

    382         else:

    383             self._handle = handle

 

OSError: [WinError 193] %1 is not a valid Win32 application

 

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From jni at fastmail.com  Wed Apr 28 22:29:34 2021
From: jni at fastmail.com (Juan Nunez-Iglesias)
Date: Thu, 29 Apr 2021 12:29:34 +1000
Subject: [scikit-learn] Invitation to lead a virtual sprint at SciPy US 2021
Message-ID: <0b2ae158-5077-415a-b464-f4a517a19ed1@www.fastmail.com>

Hi all,

I myself have come around to Ga?l's idea that mature projects like scikit-learn are not the best place for newcomers to contribute. However, since the scikit-learn team has run a lot of remote, beginner friendly sprints in the past, there are clearly exceptions! Additionally, I suspect many people on this list have smaller projects that would make for great sprint topics. So, I would like to invite scikit-learners to submit sprint ideas for SciPy US 2021 here:

https://forms.gle/w59mWNcA6JP9YA9z7

The sprint dates are July 17-18, and the sprint times are 9am-5pm US Central time.

Please feel free to contact me if you have any questions about this. I'm happy to offer guidance on running a remote sprint for those that have suitable projects but have never run their own sprints before. (Though probably Reshama and Andy are the real pros here! ?)

Thank you,

Juan.
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