On 1/24/07, Frank E Harrell Jr <f.harrell@vanderbilt.edu> 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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