Warning using " anfis " function in training of my data

8 vues (au cours des 30 derniers jours)
Mhmmd Sjj
Mhmmd Sjj le 12 Sep 2021
Commenté : Yundi Huang le 12 Nov 2021
I want to train an ANFIS structure. I have 8 inputs and one corrosponding output. When I train these data with "anfis" function, I will get the following error :
Warning: Generated rule base is large. MATLAB may run out of memory if this FIS is tuned using ANFIS.
> In genfis1 (line 161)
In genfis (line 61)
In ANFIS (line 39)
ANFIS info:
Number of nodes: 555
Number of linear parameters: 2304
Number of nonlinear parameters: 48
Total number of parameters: 2352
Number of training data pairs: 501
Number of checking data pairs: 0
Number of fuzzy rules: 256
Warning: Number of training data is smaller than number of modifiable parameters.
> In anfis>trainFIS (line 190)
In anfis>anfisWithOptionalInputs (line 326)
In anfis (line 69)
In ANFIS (line 40)
Start training ANFIS ...
And the result will go to infinity. Note that I do not want to scale my data and I need the corrosponding output which is a vector, the values of which should be between zero and one. What should I do to solve this problem ?
the following is my ANFIS code :
clc;clear;close all;
%% 1. Load Data
Data = load('data_0_to_50_smooth');
t = Data.t;
u1 = Data.u1; % Vaccination
u2 = Data.u2; % Social Distancing
u3 = Data.u3; % TreatMent Rate
states = Data.y;
states = states';
data1 = [states u1];
data2 = [states u2];
data3 = [states u3];
%% 2. Create First FiS
NumMfs = 2;
InMfsType ='trimf';
OutMfsType = 'linear';
Xin1 = data1(:,1:end-1);
Xout1 = data1(:,end);
radii = 0.2;
EpochNumber = 100;
ErrorGoal = 0.001;
StepSize =0.35;
StepSizeDecreaseRate =0.85;
StepSizeIncreaseRate = 1.15;
TrainOptions = [EpochNumber,ErrorGoal,...
StepSize,StepSizeDecreaseRate,...
StepSizeIncreaseRate];
% Fis1 = genfis1(data1,NumMfs,InMfsType,OutMfsType);
Fis1 = genfis(data1(:,1:end-1),data1(:,end));
Fis1 = anfis(data1,Fis1);
out1 = evalfis(Fis1,data(:,1:end-1),TrainOptions);
The data I used for this problem is attached.
  1 commentaire
Yundi Huang
Yundi Huang le 12 Nov 2021
hi! I met the same question, have you solve the problem yet?

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