Hi, I recently discovered scikit-learn and it looks very impressive!
I have a project that may be able to make use of scikit-learn and help me dispense with allot of custom code. The task is to identify 8 categories of features on 1024x1024 Solar images captured in 6 channels (wavelengths). A new set of 6 images arrives every 2 minutes. The current implementation is a Bayesian algorithm (mostly Python with f2py-wrapped Fortran handling a few "hot" spots). Having browsed the site documentation, I'm wondering if there is a better (all Python, simpler, easier to train, faster) approach. I would appreciate your thoughts on this. By the way, I'm a complete novice in this area. Thanks for your time. -- jv ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
