There are so many machine learning libraries for Python.
Which are good for classifying short reads with SVMs? It should include support for string kernels if I understand correctly.
It is hard for me to choose as I am new to ML. Furthermore it is difficult to compare/find all relevant options and info due to obscurity and lack of documentation.
Please advise.
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If it's string kernels you want, the shogun toolbox is for you.
Use the python_modular interface.
"also comes with a number of recent string kernels as e.g. the Locality Improved, Fischer, TOP, Spectrum, Weighted Degree Kernel (with shifts)"
Yes!
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What is the biological question you are trying to answer?
Biology? We don't need no stinking biology ... we're talking machine learning, baby! Wooo hoooo!
but if the question is just about machine learning, so it's offtopic, isn't?
It would be sad if one could not talk about string manipulation, alignment, classification, segmentation...etc in a bioinformatic forum. Don't you think? But you're right, whereas those are mandatory to analyse biological sequences, it's not a biology related question.
I agree with you, actually I find interesting how he/she will use SVM for reads classification ...
Yeah, after reading your research interests in your profile, I was actually very surprised ;-)
It is a tool used by many bioinformaticians. Furthermore, I suspect I got a better answer here than I would have anywhere else. Whether it is ok or not is up to the mods.
"Is this a pirna cluster or not?" is the question I'll attempt to answer.