I'm currently searching the web and literature for streaming classification datasets with concept drift. I've found a number of synthetic datasets where over time the important predictors either change in their "predictive" nature.
For example here is a paper with a synthetic data-set with four blocks of step style concept drift.
I've also been checking out the references on the wiki article on concept drift.
My question is.. what other REAL streaming datasets out there express concept drift in classification problems. In particular I'm looking for datasets where the set of important features completely changes with time. I've already simulated my own dataset which I vaguely discuss here. Any help is appreciated.