Attribute weighting via genetic algorithms for attribute weighted artificial immune system (AWAIS) and its application to heart disease and liver disorders problems

摘要: An increasing number of algorithms and applications have coming into scene in the field artificial immune systems (AIS) day by day. Whereas this increase is bringing successful studies, still, AIS not an effective problem solver some fields such as classification, regression, pattern recognition, etc. So far, many developed used a distance or similarity measure case instance based learning (IBL) algorithms. The efficiency IBL lies mainly weighting scheme they used. This idea was taken objective our study that we genetic to determine weights attributes then these previously Artificial Immune System (AWAIS). We evaluated performance new configuration (GA-AWAIS) on two medical datasets which were Statlog Heart Disease BUPA Liver Disorders dataset. also compared it with AWAIS for those problems. obtained classification accuracy very good respect both other common classifiers literature.