scikit-learn: machine learning in Python. Please feel free to ask specific questions about scikit-learn. Please try to keep the discussion focused on scikit-learn usage and immediately related open source projects from the Python ecosystem.
It seems
validation_curve does not really profit from multithreading/multiprocessing. I get almost same results on intel i7 (4 cores) and intel xeon (24 cores). The problem is that if the validation curve runs on the xeon machines.. it uses all cores and the machine is overloaded, which makes no sense, really :)
I'd recommend using conda and doing
conda install numpy scipy cython matplotlib pytest flake8 sphinx sphinx-gallery or something like that
but I still haven't found out why
but could also be how they are configured by default
i.e. how many threads they use etc
I have no
mkl (from conda or pip)
(so far)
from 500s to 15 seconds
@amueller this is a life saver
these envs
well stackoverflow saved your live
*life
cd doc
make html
then it will create a
_build/html folder and you can search for the index.html
@sameshl note this part of the contributing scikit-learn doc: https://scikit-learn.org/stable/developers/contributing.html#documentation
If you see ways the contributing doc can be improved while you face this "setup" issues, let us know or/and open PRs to improve the contributing docs!
As a beginner contributor to this organisation, the arrangements of the docs did feel a bit tough to navigate. I will put my thoughts about it more concisely and then open a issue and PR for the same
I am working on scikit-learn/scikit-learn#14575. So I found the corresponding example under
sklearn/metrics/pairwise.py. My question is, are the examples run in the doc building process and output is generated or I am supposed to manually write the output of the example in the docstring of a function?
you should write the output in the example. The doc build will run the code and check if the generated output is the same as the one you put there. See https://docs.python.org/3.5/library/doctest.html for more info
Is it like replacing every hidden node with a rnn cell?
I am working on scikit-learn/scikit-learn#14131 . So, I thought that I could append a note in the docstring of
KDTree regarding the issue. But I looked into sklearn/neighbors/kd_tree.pyx and it looks like KDTree is inheriting its docstring from BinaryTree. So can someone tell me an elegant way to append my note docstring to the inherited docstring of KDTree or if I could do something else to solve this issue.
Currently working on #14081.
I am supposed to create a pitfalls section which includes practices not to be followed by users. Quite confused about how should I approach it, should I create a whole new section in documentation.html or is there another way to do this??
Thanks for the help!!!
I am supposed to create a pitfalls section which includes practices not to be followed by users. Quite confused about how should I approach it, should I create a whole new section in documentation.html or is there another way to do this??
Thanks for the help!!!
Hey channel, i’ve being working on vectorizing regression tree with Numpy, and i have achieved some speed up against the cython version of sklearn. in case anyone is interested, here is the link https://github.com/yupbank/np_decision_tree#regression-with-mae