Attribute discovery - how?

Stefan_E

Hi all,

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

IngoRM

Hello Stefan,

are you already familiar with the operator "YAGGA" (an acronym for "Yet Another Generating Genetic Algorithm")? This operator was designed for the automatic detection of such attributes depending (non-linearly) on others. Maybe this helps.

Cheers,
Ingo