Re:PyML: machine learning in Python
by thomaspaine on Sunday February 22, 2009 @04:57PM
(#490897)
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
"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)"
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)"