Re: [scikit-learn] Long term roadmap and moonshot goals
If I could pitch in, it would be lovely, very lovely indeed, if scikit-learn models could: - operate on sparse data, both input and output by default - implement some kind of sparse vector representation (as in https://github.com/scikit-learn/scikit-learn/issues/8908 ) - perhaps have a unifiying numpy.array / scipy.sparse_matrix interface to give people some slack on jumping betwen [] operator conventions We would benefit from that strongly in scikit-multilearn, as when a multi-output problem is transformed to a single-output problem based on unique combinations, this representation has to be dense for scikit-learn at the moment. We end up losing some speed there. I'm sure other libraries like ex. imbalanced-learn, or scikit-multiflow would also see these as a huge thing. Best, Piotr On Sun, Jul 14, 2019 at 8:44 PM Andreas Mueller wrote: > Hi all. > At SciPy, Brian Granger raised a good point about their planning for the > Jupyter Project, which is the importance of long-term goals. > > I think it's great that we now have a detailed short-term roadmap > (https://scikit-learn.org/dev/roadmap.html). > Given that we now have about 6(!) full time people (Oliver, Jeremy, > Guillaume, Nicolas, Thomas, Adrin) on scikit-learn (GO TEAM!!), I think > it's realistic > to achieve most of these within a year or two. We have actually made > some significant progress already. > > I think now would be a good time to start thinking about a longer-term > roadmap, say 3-5 years out. > What do we want to achieve? What are realistic goals, and what are > moonshot goals? > Having a common vision and shared goals might help us with funding, but > might also help us with prioritization and motivation. > > What do you think? Do you think this is important and worth-while? > And what should our goals be? > > Best, > Andy > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -- Piotr Szymański nied...@gmail.com ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] Inclusion of an LSTM Classifier
I've created a couple of scikit-learn compatible wrappers and model generators for scikit-multilearn: http://scikit.ml/multilabeldnn.html Depends on what library you prefer, here's some examples on how to use LSTMs via: - Keras: https://medium.com/@dclengacher/keras-lstm-recurrent-neural-networks-c1f5febde03d - pyTorch: https://pytorch.org/tutorials/beginner/nlp/sequence_models_tutorial.html Just create a relevant model generating function, take a wrapper from scikit-multilearn, and put it into the scikit pipeline anyway you want. Best, Piotr Szymanski Scikit-multilearn Maintainer On Sun, Feb 17, 2019 at 7:55 PM David Burns wrote: > There is an sklearn wrapper for Keras models in the Keras library. That's > an easy way to use LSTM in sklearn. Also the sklearn estimator API is > pretty easy to figure out if you want to roll your own wrapper for any > model really. > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -- Piotr Szymański nied...@gmail.com ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] How does the random state influence the decision tree splits?
> >>> > >>> If someone knows more about this, where the random_state is used, I'd > be happy to hear it :) > >>> > >>> Also, we could then maybe add the info to the DecisionTreeClassifier's > docstring, which is currently a bit too generic to be useful, I think: > >>> > >>> > https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/tree.py > >>> > >>> > >>> random_state : int, RandomState instance or None, optional > (default=None) > >>> If int, random_state is the seed used by the random number > generator; > >>> If RandomState instance, random_state is the random number > generator; > >>> If None, the random number generator is the RandomState instance > used > >>> by `np.random`. > >>> > >>> > >>> Best, > >>> Sebastian > >>> ___ > >>> scikit-learn mailing list > >>> scikit-learn@python.org > >>> https://mail.python.org/mailman/listinfo/scikit-learn > >>> ___ > >>> scikit-learn mailing list > >>> scikit-learn@python.org > >>> https://mail.python.org/mailman/listinfo/scikit-learn > >> > >> ___ > >> scikit-learn mailing list > >> scikit-learn@python.org > >> https://mail.python.org/mailman/listinfo/scikit-learn > > ___ > > scikit-learn mailing list > > scikit-learn@python.org > > https://mail.python.org/mailman/listinfo/scikit-learn > > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -- Piotr Szymański nied...@gmail.com ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Re: [scikit-learn] Scikit Multi learn error.
Scikit-multilearn features a larger variety of models, many of which are still not above the selectiveness threshold of scikit-learn. In general, scikit-learn implements only three multi-label classifiers - BinaryRelevance, OneVsRest and ClassifierChains. And generally sklearn.multioutput is a very recent addition (2016), added 3 years after the scikit-multilearn library was started. (responding again, after joining list, i'm sorry if anyone got this twice) wt., 26 cze 2018 o 19:59 użytkownik Piotr Szymański napisał: > Scikit-multilearn features a larger variety of models, many of which are > still not above the selectiveness threshold of scikit-learn. In general, > scikit-learn implements only three multi-label classifiers - > BinaryRelevance, OneVsRest and ClassifierChains. And generally > sklearn.multioutput is a very recent addition (2016), added 3 years after > the scikit-multilearn library was started. > > wt., 26 cze 2018 o 19:40 użytkownik Fernando Marcos Wittmann < > fernando.wittm...@gmail.com> napisał: > >> Why there's a library based on Sklearn for multi classification? Sklearn >> itself can handle this ( >> http://scikit-learn.org/stable/modules/multiclass.html) >> >> On Tue, Jun 26, 2018 at 5:08 PM, Vlad Niculae wrote: >> >>> Hi Aijaz, >>> >>> You're writing to the wrong mailing list. This is the mailing list for >>> scikit-learn, not scikit-multilearn, which is a different and unrelated >>> project. You're unlikely to get an answer here; >>> I recommend following the contact information on the scikit-multilearn >>> website. >>> >>> Best of luck, >>> >>> Yours >>> Vlad >>> >>> On Tue, Jun 26, 2018, 11:04 aijaz qazi wrote: >>> >>>> Dear developer , >>>> >>>> I am working on web page categorization with http://scikit.ml/ . >>>> >>>> >>>> *Question*: I am not able to execute MLkNN code on the link >>>> http://scikit.ml/api/classify.html. I have installed py 3.6. >>>> >>>> I found scipy versions not compatible with scikit.ml 0.0.5. >>>> >>>> Which version of scipy would work with scikit.ml 0.0.5. >>>> >>>> Kindly let me know. I will be grateful. >>>> >>>> >>>> *Regards,* >>>> *Aijaz A.Qazi * >>>> ___ >>>> scikit-learn mailing list >>>> scikit-learn@python.org >>>> https://mail.python.org/mailman/listinfo/scikit-learn >>>> >>> >>> ___ >>> scikit-learn mailing list >>> scikit-learn@python.org >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> >> >> >> -- >> >> Fernando Marcos Wittmann >> MS Student - Energy Systems Dept. >> School of Electrical and Computer Engineering, FEEC >> University of Campinas, UNICAMP, Brazil >> +55 (19) 987-211302 >> >> ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
