Attribute discovery - how?
I've come across the following problem:
A data set consists of examples with coordinates in x/y (x, y being integers) and contains labels A/B/C. Problem is to predict which examples are labeled B.
Visually, I discovered that individuals with labels B are immediate neighbors of labels C: (x+1/y = C ==> x/y = . So, had I defined attributes like
label_at_(x+1)_y, label_at_(x-1)_y, label_at_x_(y+1), ...
it would have been quite easy for eg. a tree classifier to figure out which individuals had label B, given knowledge on A and C labeled examples.
However, domain knowledge does not easily imply such a neighborhood relation. Hence the question: Are there automatic ways (inside/outside RM) to discover such derieved attributes automatically?
Where do I start looking? Any pointer welcome!
Kind regards Stefan