On 6/12/07, Steven Bethard <[EMAIL PROTECTED]> wrote: > In fact, a wide variety of classifiers are used in text classification, > including Bayesian approaches, support vector machines, conditional > random fields, etc. > > > Are there any other frameworks I should be aware of? > > I have used (but not recently) Orange: > > http://www.ailab.si/orange > > I haven't used, but have been meaning to try, PyML: > > http://pyml.sourceforge.net/ > > A more recent addition (whose documentation needs work) is: > > http://montepython.sourceforge.net/ > > And here's a Summer of Code project to build an ML library: > > http://projects.scipy.org/scipy/scipy/wiki/MachineLearning > > These are all general-purpose machine learning frameworks. So they can > be applied to pretty much any classification problem (including the text > classification problems you're looking at). You just need to pick out a > set of relevant features to describe your data, and feed those features > along with your chosen labels to a machine learning algorithm. > > STeVe
Thanks Steven (and Diez), the projects you pointed me to look like great places to start. -- Evan Klitzke <[EMAIL PROTECTED]> -- http://mail.python.org/mailman/listinfo/python-list
