This function is one of the main internal functions of the package. It determines the values within the prediction phase.
1  frbs.eng(object, newdata)

object 
the 
newdata 
a matrix (m \times n) of data for the prediction process, where m is the number of instances and n is the number of input variables. 
This function involves four different processing steps on fuzzy rulebased systems.
Firstly, the rulebase (see rulebase
) validates
the consistency of the fuzzy IFTHEN rules form. Then, the fuzzification
(see fuzzifier
) transforms crisp values
into linguistic terms. Next, the inference calculates the degree of rule strengths using
the tnorm and the snorm.
Finally, the defuzzification process calculates the results of the model using the Mamdani
or the Takagi Sugeno Kang model.
A list with the following items:

the fuzzy IFTHEN rules 

a matrix to generate the shapes of the membership functions for the input variables 

a matrix of the degrees of the membership functions 

a matrix of the degrees of the rules 

a matrix of the Takagi Sugeno Kang model for the consequent part of the fuzzy IFTHEN rules 

a matrix of the predicted values 
fuzzifier
, rulebase
, inference
and defuzzifier
.
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