Question of possible application... RRS feed

  • Question

  • More of a general question on whether Infer.Net would help solve a problem with predicating whether new data fits with a previous patterns.  I think I can best illustrate the problem with some sample data.

    Accepted Parm1 Parm2 Parm3
    TRUE X X
    TRUE X
    TRUE X X X
    TRUE X X

    So what I'm trying figure out is if my new data coming in would be Accepted base on parms 1 - 3:

    ? X
    ? X X

    What's the probability that the first record should be accepted first the second one given the previous data I have?  Also, given the amount of data I have 500K rows of data with 7 different determining attributes (each attribute could have a couple of hunderd possible values) is this something that Infer.Net would handle?  In effect I'm trying to determine the outcome of a coin toss by including 7 potentially random parameters each of which has an equal weight on the outcome. I've looked at other possible technologies including probabilistic matching, SQL Match etc. without much success.

    Any Guidance would be much appreciated.

    Thursday, December 13, 2012 5:14 PM

All replies

  • You can solve this sort of problem with Infer.NET but you need to decide what your model is.

    Assuming I have understood your question correctly, one model would be a probit regression (a Bayes point machine). For each of the 7 attributes you would have an array of weights derived from some prior. Your model would use the GetItem factor to pick out the correct weight. Then sum the weights, add noise, and threshold at 0 to give a boolean output. At training you would observe which items to get, and the outcomes, and query the model for the weights. At prediction time, you would observe which items to get, use the weight posteriors as priors, and query the model for the outcomes.

    This is just one model. If you know more about your data you might be able to formulate a more customised model.


    Friday, December 14, 2012 3:55 PM