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Prospective evaluation of model prediction
Casper72
Fairly new to datamining, so this maybe a really dumb question, but I have built a model in RM based on retrospective data that appears to perform very well on both validation and test/holdout data-sets. The model is supposed to predict what will likely be the outcome on some binominal variable one year from now. So I am wondering, when I do know the actual outcome one year from now, how should I ideally evaluate my model performance? I'm thinking there must be some probabilistic uncertainty to be accounted for? Basicly I am trying to compare expected values/probabilities with real values.
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varunm1
Hello
@Casper72
Are you looking for Chi squared test? This is generally used to find a significant relationship between two same attributes(one with expected values and one with observed values).
Please inform if you need more information.
All comments
varunm1
Hello
@Casper72
Are you looking for Chi squared test? This is generally used to find a significant relationship between two same attributes(one with expected values and one with observed values).
Please inform if you need more information.
Casper72
Thank you
@varunm1
Brilliant. Should have thought of that.
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