New to machine learning and have been reading about ensemble modelling. A statement that keeps reappearing is: "Ensemble models work better when we ensemble models of low correlation."
I've seen examples, but I can't find an explanation for why this case? Could anyone shed some light?
Best Answer
You wake up in the morning and want to decide whether to take an umbrella with you when leaving. You look at the weather forecast from five newspapers on the assumption that their combined prediction would be more accurate than the prediction of only one of them. Does your assumption still hold if instead of looking at the prediction from five different newspapers (possibly using different weather models) you look at the predictions of five copies of the same newspaper?