What Is Fuzzy Logic?

anfis and the ANFIS Editor GUI
To view a graphical representation of the initial FIS model structure, click
Structure.
Training the FIS
After loading the training data and generating the initial FIS structure, you
can start training the FIS.
The following steps show you how to train the FIS.
1 In Optim. Method, choose hybrid or backpropaga as the optimization
method.
The optimization methods train the membership function parameters to
emulate the training data.
Note The hybrid optimization method is a combination of least-squares
and backpropagation gradient descent method.
2 Enter the number of training Epochs and the training Error Tolerance
to set the stopping criteria for training.
The training process stops whenever the maximum epoch number is
reached or the training error goal is achieved.
3 Click Train Now to train the FIS.
This action adjusts the membership function parameters and displays the
error plots.
Examine the error plots to determine overfitting during the training. If
you notice the checking error increasing over iterations, it indicates model
overfitting. For examples on model overfitting, see “ANFIS Editor GUI
Example 1: Checking Data Helps Model Validation” on page 2-114 and
“ANFIS Editor GUI Example 2: Checking Data Does Not Validate Model” on
page 2-124.
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