I'm dealing with a supervized binary classification issue. My dataset is composed of 1500 individuals, living in 600 households. I have approximately 4000 variables to classify my subjects as "infected/uninfected".
I was wondering how would it be possible to account for the hierarchical nature of my data in a data mining classification method, such as CART, MARS or other methods, as it is done for instance in mixed-effects models ? I suppose that the hierarchical structure of the data cannot be ignored, because the risk of a individual to be infected is higher is there is already an infected individual in his household.