

PyML: machine learning in Python - rogercosseboom
http://pyml.sourceforge.net/

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kaiser
I am currently playing around with it. Decent support vector machine
implementation. However, I have some problems with it. It is by far not as
hugh as weka <http://www.cs.waikato.ac.nz/ml/weka/> It is in python (big plus)
and seems to be easily hacked for online classification. I like
<https://mlpy.fbk.eu/> a bit better, as it has also a decent integrated
Nearest Neighbor (ok, ok this one is not hard to implement on your own) and
FDA + DWT (awsome).

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lliiffee
Hey, what do FDA and DWT stand for? (Sorry, that link doesn't work for me.)
Thanks!

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mcxx
Google, being a good friend of mine, didn't mind me asking. His answer: Fisher
Discriminant Analysis (FDA), Discrete Wavelet Transform (DWT). I'll introduce
you: <http://google.com>

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lliiffee
I did search for DWT. I don't understand how wavelets would be used in this
context, so I was hoping for some verification.

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thomaspaine
PySVM might have been a better name, since it looks like it only does SVM and
kernel methods. I haven't used this package, but I'll recommend libsvm and
liblinear because they're fast and have wrappers for just about every language
you want, including Java, Ruby, Matlab, and Python
<http://www.csie.ntu.edu.tw/~cjlin/libsvm/#python>

If you're doing large scale linear classification, liblinear is especially
awesome and fast. <http://www.csie.ntu.edu.tw/~cjlin/liblinear/>

EDIT: From the PyML documentation:

"By default the libsvm solver is used in training. To use the PyML SMO
optimizer either set the optimizer attribute to ’mysmo’ or instantiate an svm
instance as svm.SVM(optimizer = ’mysmo’). Note that for a non-vector dataset,
the default libsvm optimizer cannot be used and the PyML native SMO
implementation is automatically used instead (it is slower than libsvm so is
not the default)"

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kaiser
Yes, great lib (totally forget about the python bindings). I was using it
under matlab works like a charm

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jacquesm
One serious problem of HN is that the amount of good stuff on here greatly
exceeds my capacity for absorbing it all... Roughly one week goes by and I
have at least another months worth of reading added to my list.

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mjtokelly
<http://www.ailab.si/orange/>

This is the most thorough Python machine learning package I know of. Includes
SVM.

Lots of tutorials, too, and a visual development environment (if that's your
style).

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metaguri
Wow, sounds impressive, but that link isn't working for me unfortunately! Do
you know of a mirror?

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mjtokelly
Blast, it was fine just two hours ago.

[http://74.125.47.132/search?q=cache:iqMjX8uGgroJ:www.ailab.s...](http://74.125.47.132/search?q=cache:iqMjX8uGgroJ:www.ailab.si/orange/+python+orange&hl=en&ct=clnk&cd=1&gl=us)

Google cache, to whet your appetite...

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mcroydon
If only there were some good non-GPL machine learning libraries for Python...

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pskomoroch
There is a start at it here:

<http://www.scipy.org/scipy/scikits/wiki/MachineLearning>

Still some active development, but needs more people:

[http://projects.scipy.org/scipy/scikits/browser/trunk/learn/...](http://projects.scipy.org/scipy/scikits/browser/trunk/learn/scikits/learn)

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apu
Has anyone used this? Care to share your experience?

