I have a feature array of around 4000 elements, extracted from one source. On this array I've extracted 7 more feature from other source and now I basically have a 4007 feature array from each data point. I am trying to classify these data points based on this feature array, basically doing a 1NN with manhattan distance.
However since I am really bad at maths I'm not sure how to weigh this so my 7 elements can actually help in regards to this. It feels like those 4000 elements are way more important and on distance calculation the other 7 are insignificant.
I've also given this input to a Neural Network and i'm wondering if I need to preprocess something there aswell or can I just give it the 4007 elements to the input neurons?
I've done feature-scaling but I guess that is irrelevant to the problem I'm asking.