On 1/24/07, Frank E Harrell Jr <[EMAIL PROTECTED]> wrote:
> Why 0.5?
The probability has to adjusted based on some hit and trials. I just
mentioned it as an example
>
> Those are improper scoring rules that can be tricked. If the outcome is
> rare (say 0.02 incidence) you could just predict that no one will have
> the outcome and be correct 0.98 of the time. I suggest validating the
> model for discrimination (e.g., AUC) and calibration.
I just have to calculate precision/recall for rare outcome. If the positive
outcome is rare ( say 0.02 incidence) and I predict it to be negative all
the time, my recall would be 0, which is bad. So, precision and recall can
take care of skewed data.
Frank
>
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