FIR.DM updating function

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Description

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, FIR.DM.

Usage

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DM.update(data.train, rule.data.num, miu.rule, func.tsk, varinp.mf,
  step.size = 0.01, def)

Arguments

data.train

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.

rule.data.num

a matrix containing the rulebase. Its elements are integers, see rulebase.

miu.rule

a matrix with the degrees of rules which is a result of the inference.

func.tsk

a matrix of parameters of the functions on the consequent part of the Takagi Sugeno Kang model.

varinp.mf

a matrix of parameters of the membership functions of the input variables.

step.size

the step size of the descent method, between 0 and 1.

def

a matrix which is obtained from the defuzzification. Please have a look at defuzzifier.

See Also

frbs.learn, predict, and FIR.DM.

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