🌐 Mailman 3 July 2016 - scikit-learn - python.org

Declaring numpy and scipy dependencies?
by Andreas Mueller Sept. 1, 2016

Sept. 1, 2016

Hi all. I think since the pipy ecosystem improved a lot, we should properly declare the scipy and numpy dependencies, so that ``pip install scikit-learn`` works properly. The argument why we did not do this previously was that this would try to download and build numpy and scipy, which are pretty much guaranteed to fail / result in a very slow installation. This is no longer true. Any opinions? Andy

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0.18?
by Joel Nothman Aug. 22, 2016

Aug. 22, 2016

Has there been talk about a release? We've long-since merged the big changes to CV. Among the things seeming unfinished there is that where `cv` is available, `fit` should also support a `labels` parameter. That's not available in RFECV etc. There are some other nice features in the next release too, and I think we should move towards putting them out there. Should we start tagging issues in and out of the 0.18 milestone?

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Is there any official position on PEP484/mypy?
by Daniel Moisset Aug. 4, 2016

Aug. 4, 2016

Hi, [If you're also on the numpy mailing list and get a similar version of the message, I apologise for that] I work at Machinalis were we use a lot of scikit-learn (and the pydata stack in general). Recently we've also been getting involved with mypy, which is a tool to type check (not on runtime, think of it as a linter) annotated python code (the way of annotating python types has been recently standarized in PEP 484). As part of that involvement we've started creating type annotations for the Python libraries we use most, which include both numpy and scikit-learn. Mypy provides a way to specify types with annotations in separate files in case you don't have control over a library, so we have created an initial proof of concept for numpy at [1], and we are actively improving it. You can find some additional information about it and some problems we've found on the way at this blogpost [2]. We were planning to also start some work on scikit-learn (which has a much larger surface area than numpy, so probably focusing on small parts for now); we had to start with numpy anyway given that SKL depends on it. What I wanted to ask is if the people involved on the SKL project are aware of PEP484 annotations and if you have some interest in starting using them. The main benefit is that annotations serve as clear (and automatically testable) documentation for users, and secondary benefits is that users discovers bugs more quickly and that some IDEs (like pycharm) are starting to use this information for smart editor features (autocompletion, online checking, refactoring tools); eventually tools like jupyter could take advantage of these annotations in the future. And the cost of writing and including these are relatively low. We're doing the work anyway, but contributing our typespecs back could make it easier for users to benefit from this, and for us to maintain it and keep it in sync with future releases. If you've never heard about PEP484 or mypy (it happens a lot) I'll be happy to clarify anything about it that might helpunderstand this situation Thanks! D. [1] https://github.com/machinalis/mypy-data [2] http://www.machinalis.com/blog/writing-type-stubs-for-numpy/ -- Daniel F. Moisset - UK Country Manager www.machinalis.com Skype: @dmoisset

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error from import sklearn
by Lifan Xu July 29, 2016

July 29, 2016

Hi guys, I am sorry to bother you. But I have a question about using scikit-learn in ubuntu. I installed scikit using: sudo apt-get install build-essential python-dev python-numpy python-numpy-dev python-scipy libatlas-dev g++ python-matplotlib ipython sudo pip install -U scikit-learn However, when I try to use scikit, I got this error: Python 2.7.6 (default, Jun 22 2015, 17:58:13) [GCC 4.8.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from sklearn import datasets Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python2.7/dist-packages/sklearn/__init__.py", line 57, in <module> from .base import clone File "/usr/local/lib/python2.7/dist-packages/sklearn/base.py", line 11, in <module> from .utils.fixes import signature File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/__init__.py", line 11, in <module> from .validation import (as_float_array, File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py", line 16, in <module> from ..utils.fixes import signature File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/fixes.py", line 322, in <module> from ._scipy_sparse_lsqr_backport import lsqr as sparse_lsqr File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/_scipy_sparse_lsqr_backport.py", line 58, in <module> from scipy.sparse.linalg.interface import aslinearoperator File "/usr/lib/python2.7/dist-packages/scipy/sparse/linalg/__init__.py", line 108, in <module> from .isolve import * File "/usr/lib/python2.7/dist-packages/scipy/sparse/linalg/isolve/__init__.py", line 6, in <module> from .iterative import * File "/usr/lib/python2.7/dist-packages/scipy/sparse/linalg/isolve/iterative.py", line 11, in <module> from scipy.lib.decorator import decorator File "/usr/lib/python2.7/dist-packages/scipy/lib/decorator.py", line 39, in <module> import sys, re, inspect File "/usr/lib/python2.7/inspect.py", line 37, in <module> import dis File "/usr/lib/python2.7/dis.py", line 7, in <module> from opcode import __all__ as _opcodes_all ImportError: cannot import name __all__ Anyone knows how to fix this problem? Thanks!

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CI permissions
by Andreas Mueller July 29, 2016

July 29, 2016

Hey all. So I think I messed with the CI a bit too much yesterday. After looking into the organization permissions a bit more, I saw that any app that is authorized on github by any of the devs will automatically be authorized for the organization. That seems pretty bad. So I change that default to each app needing to be authorized explicitly for the organization. Clearly I wasn't thinking, because that broke CI. I gave permissions back to the CI services, but they are not all linked to my account. Olivier, can you check for coveralls and circleci? I think you have these accounts. Appveyor and travis are working again. Sorry for the inconvenience, Andy

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Blog post about Cython fused type pointer that can help reduce duplicated code
by lin yenchen July 26, 2016

July 26, 2016

Hello guys, here is a blog post - Using Function Pointer with Fused Types to Maximize Code Reusability <http://blog.yclin.me/gsoc/2016/07/17/Function-Pointer/> I wrote to document my findings during GSoC. Hope this help, especially for people who is trying to add fused types to BLAS-based and similar fused type function calls. Please feel free to leave some comments so I can improve it. And thanks Joel for the early review. Best, YenChen Lin

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Three new scikit-learn-contrib projects
by Mathieu Blondel July 25, 2016

July 25, 2016

Hi everyone, We are pleased to announce that three new projects recently joined scikit-learn-contrib! * imbalanced-learn: https://github.com/scikit-learn-contrib/imbalanced-learn Python module to perform under sampling and over sampling with various techniques. * polylearn: https://github.com/scikit-learn-contrib/polylearn Factorization machines and polynomial networks for classification and regression in Python. * forest-confidence-interval: https://github.com/scikit-learn-contrib/forest-confidence-interval Confidence intervals for scikit-learn forest algorithms. We thank the respective authors for their neat contribution to the scikit-learn ecosystem! Cheers, Mathieu

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about svdd model
by fengyanghe July 23, 2016

July 23, 2016

Hi guys: I'm trying to solve an one class classification problem. It seems to be not very good by using one class svm of scikit-learning. I want to try support vector data description(svdd) mothed. I'm wondering where I can get the code of the svdd. thanks.

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Re: [scikit-learn] [Scikit-learn-general] How to run scikit-learn test individually.
by Kyle Kastner July 22, 2016

July 22, 2016

you can call nosetests with a script name or even a function name e.g. nosetests test_init.py:test_import_skl will test the test_import_skl function inside test_init.py nosetests test_init.py would run all the tests in that file. On Fri, Jul 22, 2016 at 1:59 PM, Kyle Kastner <kastnerkyle(a)gmail.com> wrote: > you can call nosetests with a script name or even a function name e.g. > > nosetests test_init.py:test_import_skl > > will test the test_import_skl function inside test_init.py > > nosetests test_init.py > > would run all the tests in that file. > > On Fri, Jul 22, 2016 at 11:33 AM, Boxiang Sun <daetalusun(a)gmail.com> wrote: >> Hi all. >> >> I posted this question in IRC once, but maybe due to time zone or other >> reason. I didn't got answer yet(maybe I missed). >> >> I am trying to let scikit-learn can work in Pyston. I already finished >> NumPy, SciPy support in Pyston. >> >> When I try to run scikit-learn test suite by `python -c "import nose; >> nose.main()" -v sklearn`. Most of were fine. But I encountered one segfault, >> the back trace said it is in `sklearn/metrics/tests/test_pairwise.py`. >> >> But if I try to run that script individually by `python >> scikit-learn/sklearn/metrics/tests/test_pairwise.py`, like what I did when >> try to support NumPy and SciPy. That command didn't output anything, no >> segfault, no output. Try to use this way to run other test files will get >> same empty output. >> >> So how to run the sk-learn test individually and reproduce errors? Not by >> run the whole test suite. >> >> Regards, >> Sun >> >> ------------------------------------------------------------------------------ >> What NetFlow Analyzer can do for you? Monitors network bandwidth and traffic >> patterns at an interface-level. Reveals which users, apps, and protocols are >> consuming the most bandwidth. Provides multi-vendor support for NetFlow, >> J-Flow, sFlow and other flows. Make informed decisions using capacity >> planning >> reports.http://sdm.link/zohodev2dev >> _______________________________________________ >> Scikit-learn-general mailing list >> Scikit-learn-general(a)lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >>

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How to get the most important features from a RF efficiently
by Raphael C July 21, 2016

July 21, 2016

I have a set of feature vectors associated with binary class labels, each of which has about 40,000 features. I can train a random forest classifier in sklearn which works well. I would however like to see the most important features. I tried simply printing out forest.feature_importances_ but this takes about 1 second per feature making about 40,000 seconds overall. This is much much longer than the time needed to train the classifier in the first place? Is there a more efficient way to find out which features are most important? Raphael On 21 July 2016 at 15:58, Nelson Liu <nfliu(a)uw.edu> wrote: > Hi, > If I remember correctly, scikit-learn.org is hosted on GitHub Pages (so the > maintainers don't have control over downtime and issues like the one you're > having). Can you connect to GitHub, or any site on GitHub Pages? > > Thanks > Nelson > > On Thu, Jul 21, 2016, 07:52 Rahul Ahuja <rahul.ahuja(a)live.com> wrote: >> >> Hi there, >> >> >> Sklearn website has been down for couple of days. Please look into it. >> >> >> I reside in Pakistan, Karachi city. >> >> >> >> >> >> >> Kind regards, >> Rahul Ahuja >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn(a)python.org >> https://mail.python.org/mailman/listinfo/scikit-learn > > > _______________________________________________ > scikit-learn mailing list > scikit-learn(a)python.org > https://mail.python.org/mailman/listinfo/scikit-learn >

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