Hi Everyone,

I am looking for some suggestions on a problem that I am currently facing.

I have a set of sensor say S1-S100 which is triggered when some event E1-E20 is performed. Assume, normally E1 triggers S1-S20, E2 triggers S15-S30, E3 triggers S20-s50 etc and E1-E20 are completely independent events. Occasionally an event E might trigger any other unrelated sensor.

I am using ensemble of 20 svm to analyze each event separately. My features are sensor frequency F1-F100, number of times each sensor is triggered and few other related features.

I am looking for a technique that can reduce the dimensionality of the sensor feature(F1-F100)/ or some techniques that encompasses all of the sensor and reduces the dimension too(i was looking for some information theory concept for last few days) . I dont think averaging, maximization is a good idea as I risk loosing information(it did not give me good result).

Can somebody please suggest what am I missing here? A paper or some starting idea...

Thanks in advance.