Monday, February 05, 2007

Poll: Model Selection

In the spirit of the latest posts on model selection, here is a poll to get feedback on that question. I understand that few practitioners always use the exact same metric to select models. This poll is only asking which one is used most often when you need a single number to select models (and input variables don't matter as much).



Create polls and vote for free. dPolls.com
at

2 comments:

  1. Will Dwinnell6:34 AM

    For classification problems, my usual practice is to assess class separation via AUC (area under the ROC curve) and probability accuracy via informational loss or MSE.

    For numeric problems, I lean toward mean absolute error, or, when relative error is more important, mean absolute percent error.

    ReplyDelete
  2. Anonymous8:37 PM

    For risk scoring it's nearly always KS (Kolmogorov-Smirnov). For forecasting, MAPE.

    ReplyDelete