The role of this function is to update the parameters of the fuzzy inference rules by descent method (FIR.DM).
This function is called by the main function of the FIR.DM method,
DM.update(data.train, rule.data.num, miu.rule, func.tsk, varinp.mf, step.size = 0.01, def)
a matrix (\(m \times n\)) of normalized data, where \(m\) is the number of instances and \(n\) is the number of variables; the last column is the output variable.
a matrix containing the rulebase. Its elements are integers, see
a matrix with the degrees of rules which is a result of the
a matrix of parameters of the functions on the consequent part of the Takagi Sugeno Kang model.
a matrix of parameters of the membership functions of the input variables.
the step size of the descent method, between 0 and 1.
a matrix which is obtained from the defuzzification. Please have a look at