document: Formalising optimal feature weight setting in case based diagnosis as linear programming problems Many approaches to case based reasoning -LRB- CBR -RRB- exploit feature weight setting algorithms to reduce the sensitivity to distance functions . We demonstrate that optimal feature weight setting in a special kind of CBR problems can be formalised as linear programming problems . Therefore , the optimal weight settings can be calculated in polynomial time instead of searching in exponential weight space using heuristics to get sub-optimal settings . We also demonstrate that our approach can be used to solve classification problems
doc_bio_tags: O B I I I O B I I O B I O O O O B I I O O O O O O O O O O O O O B I O O O O B I I I O O O O O O O O O O O B I O O O O O O O O O O O O B I O O B O B I I O B O O O O O O O O O O O O O O O O B O
extractive_keyphrases: optimal feature weight setting case based diagnosis linear programming case based reasoning distance functions polynomial time searching exponential weight space classification heuristics