Tell me more ×
Cross Validated is a question and answer site for statisticians, data analysts, data miners and data visualization experts. It's 100% free, no registration required.
up vote 2 down vote favorite

I want to create a binary model which predicts whether someone has improved his state. I am testing possible variables as explanatory variables in order to make some recommendations. Now my binary model is quite weak, AUC is around 0.6 and there are hardly any cases predicted above 0.5 in the test set.

Now I could simply improve my model by including the previous state which is highly correlated with improvement, but for me this is too obvious. It might 'kick out' other explanatory (more actionable) variables.

So now I am faced with this question of whether to go for accuracy or simpler/actionable model.

What do you recommend?

share|improve this question
btw, are you THE Dirk Nachbar ? – steffen Aug 8 '12 at 14:09
It seems that you are not a newb. So what is concerning you ? What is your goal ? If you want to maximize accuracy no matter what, go for it (as Michael said). If you are looking for insights what might cause improvement, in the sense that experts can use the information to implement new methods for grade improvement, calculate predictor importance additionally. Calculating the importance conditional on state predictor might lead to new insights. Finally, it might be that the important predictors are missing, e.g. social factors. – steffen Aug 9 '12 at 7:04
In summary, the problem of selecting a method often is caused by not knowing what you actually want to achieve. Any comment or clarification on all this ? – steffen Aug 9 '12 at 7:08
yes I am THE Dirk Nachbar – Dirk Nachbar Aug 24 '12 at 8:17
show 1 more comment

1 Answer

up vote 1 down vote

I think you should use whatever are the best predictors. If the previous state is available and makes practical sense to use in the model I see no reason to leave it out.

share|improve this answer
We have included the previous state now as some other predictors were affected by its omission. – Dirk Nachbar Aug 24 '12 at 8:18

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.