

Machine Learning Cheat Sheet (for scikit-learn) - stadeschuldt
http://peekaboo-vision.blogspot.de/2013/01/machine-learning-cheat-sheet-for-scikit.html

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StavrosK
I had a short look at scikit-learn for a hobby classifier I'm writing (it aims
to email me interesting HN articles so I don't waste much time reading things
I don't like or refreshing HN all the time), and it looks fantastic. I haven't
looked at the code or used it very much, but the documentation is very
thorough and informative, and the library itself is very extensive.

There are some things missing, (e.g. The naive Bayes implementation is
offline, which is not very useful to me), but the library is fantastic for
prototyping, at least. Congratulations to the people working on it!

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t3kcit
Thanks :) We should really add online naive Bayes and it would be really easy.
But no-one got around to it yet :-/ Feel free ;)

~~~
StavrosK
I just might! I'll issue a pull request if I do, thanks!

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gms
For predicting structure (which takes you to 'tough luck' in the chart as it's
not implemented in scikit-learn), you can use structured SVM's through either
SVM-Struct
([http://www.cs.cornell.edu/people/tj/svm_light/svm_struct.htm...](http://www.cs.cornell.edu/people/tj/svm_light/svm_struct.html))
or JLIS
([http://flake.cs.uiuc.edu/~mchang21/softwares/JLIS/indirect.h...](http://flake.cs.uiuc.edu/~mchang21/softwares/JLIS/indirect.html)).

Though note that both libraries are free for non-commercial use only.

~~~
t3kcit
Or you could use pystruct: <https://github.com/amueller/pystruct> But I saved
that for another blog post ;)

That is BSD licensed and pure Python, has some more feature than SVMstruct but
is not as optimized (yet).

~~~
gms
I had no idea your project existed; thanks for sharing.

~~~
t3kcit
I did a another post on that one. [http://peekaboo-
vision.blogspot.de/2013/01/pystruct-more-str...](http://peekaboo-
vision.blogspot.de/2013/01/pystruct-more-structured-prediction.html) The post
still needs some more detail, though.

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aidos
I know nothing much about machine learning (though I was digging around scikit
learn earlier this evening) but this is a diagram I can appreciate :)

