I am cleaning data that I will use with machine learning prediction algorithms.
Several of my variables in my data set are sums of other variables. eg) given variables x1, x2, x3, x3=x2+x1 or even x4= x5+x6+...x10.
I feel like I should remove these variables but am not sure. Is there any reason to keep variables like this or should you always remove these kinds of variables? Related question, how does collinearity affect your machine learning algorithm?