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need help... can't predict hte other clas...
hello, I just moved this topic here because someone advises me to post this message here, since it's more suitable. ;D
and now, I'm having some problems now with my dataset...
My dataset consist of binominal label (yes and no).
I use all kind of tree and all type of validation and attribute selection, but only this appear in my dataset,
it means that the model can't predict the other class (yes). the records with class labeled "yes" is only about 20% from the entire dataset (about 5200 out of 27000 overall). so the accuracy seems good (about 80%), but it can be "harakiri" if I apply this model.
what should I do? I desperately need for help.... :-[
Thank you very much for your reply...
Regards,
Dimas Yogatama
and now, I'm having some problems now with my dataset...
My dataset consist of binominal label (yes and no).
I use all kind of tree and all type of validation and attribute selection, but only this appear in my dataset,
it means that the model can't predict the other class (yes). the records with class labeled "yes" is only about 20% from the entire dataset (about 5200 out of 27000 overall). so the accuracy seems good (about 80%), but it can be "harakiri" if I apply this model.
what should I do? I desperately need for help.... :-[
Thank you very much for your reply...
Regards,
Dimas Yogatama
0
Answers
did you already try to reweight your examples? You might assign a higher weight on the "yes" examples. This is possible by generating a new attribute and assign the role "weight". You can do this either with the Generate Weight (Stratification) if you want to assign both classes an equal value or do it with a process. Here's a small example process for this: Greetings,
Sebastian
I'll try it first