On Tue, Nov 06, 2018 at 02:33:56PM -0500, Rick Hedin wrote: > Hi. Could you give me a reading on whether MLpack is an appropriate tool > for what I want to do? Too often, you start down a path, and after a few > weeks you realize "Oh. I shouldn't be doing this."
Hey there Rick, Always good to check first. :) I'll do my best to provide useful answers... > I would like to put an AI process on the message stream, transparent > to other uses of the message stream. When one of our operators marks > a transaction as "possibly fraudulent," that would be a data item for > the AI process. When they later mark it "definitely fraudulent" or > "definitely not fraudulent," those are also data items for the AI. > Eventually, the AI would be able to add additional tags in the record > "AI suspects this transaction is fraudulent" or "AI suspects this > transaction is not fraudulent," along with "AI confidence is xxx%." > > The nice thing about this setup is nobody has to spend hours training it. > The data stream provides both data, and judgement on the data. > > So, is this a good application for MLpack? Or is it more intended for > other purposes, and a different software suite is more appropriate? So, I think mlpack could work for this but keep in mind a lot of the system development here will be preparing the input to give to mlpack so that mlpack can make the predictions. mlpack does all its predictions on numeric data; so, for instance, if you have a dataset full of words, you'll need to convert these words to numeric values as one-hot encoding, or perhaps by an embedding or TF-IDF or something like this. Note that mlpack does have Python bindings, so if you're working from Python it might fit really nicely into a Python workflow. Hope that this is helpful! Thanks, Ryan -- Ryan Curtin | "Avoid the planet Earth at all costs." [email protected] | - The President _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
