We have the feeling that behavior of a device in terms of continuous variables (fans speeds, temperatures, voltages, ...) has influence on rare events happening (components failures).
I now have to build a predictive model for that, to proof the influence.
Those continuous features are given as time series, and events are punctual.
I've made a model based on descriptive statistics of those variable (see this question) with decision tree, random forest, adaboost, and clustering but it doesn't works. I will still improve by balancing classes, but I'm convinced it is not the best approach.
I'm pretty sure that there are nicer algorithms for such predictions (this is quite common problem), but I don't find anything.
Do you have ideas?
Thanks a lot
PS: I'm working with Python and cython