View source: R/FNN.FunctionCollection.R
The role of this function is to update parameters in the ANFIS method.
This function is called by the main function of the ANFIS method, ANFIS
.
1 2 | ANFIS.update(data.train, def, rule.data.num, miu.rule, func.tsk, varinp.mf,
step.size = 0.01)
|
data.train |
a matrix (m \times n) of normalized data for the training process, where m is the number of instances and n is the number of variables; the last column is the output variable. |
def |
a predicted value |
rule.data.num |
a matrix containing the rule base in integer form. |
miu.rule |
a matrix with the degrees of rules. See |
func.tsk |
a matrix of parameters of the function on the consequent part using the Takagi Sugeno Kang model. |
varinp.mf |
a matrix of parameters of membership functions of the input variables. |
step.size |
a real number between 0 and 1 representing the step size of the gradient descent. |
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