Prospective evaluation of model prediction

Casper72
Casper72 New Altair Community Member
edited November 2024 in Community Q&A
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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Best Answer

  • varunm1
    varunm1 New Altair Community Member
    Answer ✓
    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.

Answers

  • varunm1
    varunm1 New Altair Community Member
    Answer ✓
    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
    Casper72 New Altair Community Member
    Thank you @varunm1

    Brilliant. Should have thought of that.

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