//--- // Load FIS (Fuzzy Inference System) //--- FIS fis = FIS.load("fcl/qualify.fcl"); RuleBlock ruleBlock = fis.getFunctionBlock().getRuleBlock(); //--- // Create a list of parameter to optimize //--- ArrayList parameterList = new ArrayList(); // Add variables. // Note: Fuzzy sets' parameters for these // variables will be optimized Parameter.parameterListAddVariable(parameterList , fis.getVariable("scoring")); Parameter.parameterListAddVariable(parameterList , fis.getVariable("credLimMul")); // Add every rule's weight for( Rule rule = ruleBlock ) Parameter.parameterListAddRule(parameterList, rule); //--- // Create an error function to be // optimzed (i.e. minimized) //--- ErrorFunctionQualify errorFunction = new ErrorFunctionQualify(); //--- // Optimize (using 'Delta jump optimization') //--- OptimizationDeltaJump optimizationDeltaJump = new OptimizationDeltaJump(ruleBlock , errorFunction, parameterList); // Number optimization of iterations optimizationDeltaJump.setMaxIterations(20); optimizationDeltaJump.optimize(true);

The error funcion (in this particular case, ErrorFunctionQualify) can be just any error function, the structure for the code should be like this:

public class ErrorFunctionQualify extends ErrorFunction { public double evaluate(RuleBlock ruleBlock) { double error; // Caculate your desired error here... return error; } }