MembershipFunction

MembershipFunction-class


Represent a generic virtual S4 MembershipFunction class, for fuzzy further
redefinition. The actual subclases available are GaussianMF,
NormalizedGaussianMF and BellMF.


The package implements ANFIS Type 3 Takagi and Sugeno's fuzzy
if-then rule network with the following features: (1) Independent number of
membership functions(MF) for each input, and also different MF extensible
types. (2) Type 3 Takagi and Sugeno's fuzzy if-then rule (3) Full Rule
combinations, e.g. 2 inputs 2 membership funtions -> 4 fuzzy rules (4)
Hibrid learning, i.e. Descent Gradient for precedents and Least Squares
Estimation for consequents (5) Multiple outputs.

Cristobal Fresno

anfis

Adaptive Neuro Fuzzy Inference System in R

MembershipFunction-class function

 <dl>
<dt><code>parameters</code></dt><dd>named numeric vector with parameters of Membership Function.</dd> <dt><code>nParameters</code></dt><dd>integer with the number of parameters for validity check.</dd> <dt><code>name</code></dt><dd>character The description of the membership function.</dd> <dt><code>expression</code></dt><dd>expression object just to display purposes.</dd> </dl>

Slots

 MembershipFunction S4 class includes the following functions:
<dl>
 <dt>show/print</dt><dd>generic output of the object.</dd> <dt>"[", "[&lt;-"</dt><dd>getter and setter of the parameters values.</dd> <dt>evaluateMF</dt><dd>return membership value at x.</dd> <dt>derivateMF</dt><dd>return the derivate membership at x.</dd> </dl> 

MembershipFunction-class: MembershipFunction S4 class

Description

Arguments

Slots

Functions

See Also