Quote:
Originally Posted by GraceLAX
If an algorithm always converges would the Pr(f(x) ne g(x)) = 0?
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I believe you will need to generate a separate set of test data to process and determine the error rate. Don't update the weights when processing the test data, just process each data point and determine whether it was correct or not. Aggregate those results and you should have your classifier error rate.
BTW: This is how I did it which I guess shouldn't necessarily be confused with the correct way of doing it
