It is clear that in almost any classification task, the attributes
that characterize the objects to be classified are not equally
important. Weights for the values of the rules obtained by a
learning classifier system are evolved in present paper in order
to find the degree to which attributes influence classification
classes. The method is tested on a real world problem, i.
e. diabetes diagnosis; results outline considerable
improvements.