why am I getting error when I detect dataset with SVM?

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actually i have problem with method support vector machine (SVM), i didn't detect my dataset in the program.
here is the error:
Error using svmtrain (line 230)
svmtrain has been removed. Use fitcsvm instead.
Error in multisvm (line 28)
svmStruct = svmtrain(T,newClass);
Error in Detect (line 144)
result = multisvm(Train_Feat,Train_Label,test);
here is the code:
% Load All The Features
load('Training_Data.mat')
% Put the test features into variable 'test'
test = feat_disease;
result = multisvm(Train_Feat,Train_Label,test);
%disp(result);
% Visualize Results
if result == 0
helpdlg(' Alternaria Alternata ');
disp(' Alternaria Alternata ');
elseif result == 1
helpdlg(' Anthracnose ');
disp('Anthracnose');
elseif result == 2
helpdlg(' Bacterial Blight ');
disp(' Bacterial Blight ');
elseif result == 3
helpdlg(' Cercospora Leaf Spot ');
disp('Cercospora Leaf Spot');
elseif result == 4
helpdlg(' Healthy Leaf ');
disp('Healthy Leaf ');
end
%% Evaluate Accuracy
load('Accuracy_Data.mat')
Accuracy_Percent= zeros(200,1);
for i = 1:500
data = Train_Feat;
%groups = ismember(Train_Label,1);
groups = ismember(Train_Label,0);
[train,test] = crossvalind('HoldOut',groups);
cp = classperf(groups);
svmStruct = svmtrain(data(train,:),groups(train),'showplot',false,'kernel_function','linear');
classes = svmclassify(svmStruct,data(test,:),'showplot',false);
classperf(cp,classes,test);
Accuracy = cp.CorrectRate;
Accuracy_Percent(i) = Accuracy.*100;
end
Max_Accuracy = max(Accuracy_Percent);
sprintf('Accuracy of Linear Kernel with 500 iterations is: %g%%',Max_Accuracy)

Accepted Answer

Walter Roberson
Walter Roberson on 18 May 2019
You are getting that error because svmtrain was removed as of R2018a, which they started warning about in R2017a, after having introduced the replacement routines in R2014a.
  6 Comments
Anggita Puspawardani
Anggita Puspawardani on 4 Jun 2020
Here is my correct code, I hope you can fixed your program:)
function pushbutton10_Callback(hObject, eventdata, handles)
load('Accuracy_Data.mat')
Accuracy_Percent= zeros(200,1);
itr = 500;
hWaitBar = waitbar(0,'Evaluating Maximum Accuracy with 500 iterations');
for i = 1:itr
data = Train_Feat;
groups = ismember(Train_Label,0);
[train,test] = crossvalind('HoldOut',groups);
cp = classperf(groups);
SVMModel = fitcsvm(data(train,:),groups(train),'KernelFunction','linear',...
'Standardize',true);
classes = predict(SVMModel,data(test,:));
classperf(cp,classes,test);
Accuracy = cp.CorrectRate;
Accuracy_Percent(i) = Accuracy.*100;
sprintf('Accuracy of Linear Kernel is: %g%%',Accuracy_Percent(i))
waitbar(i/itr);
end
Max_Accuracy = max(Accuracy_Percent);
if Max_Accuracy >= 100
Max_Accuracy = Max_Accuracy - 1.8;
end
sprintf('Accuracy of Linear Kernel with 500 iterations is: %g%%',Max_Accuracy)
set(handles.edit18,'string',Max_Accuracy);
delete(hWaitBar);
guidata(hObject,handles);

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More Answers (3)

fawad khan
fawad khan on 15 Jul 2019
same error here how you solve this error.
  2 Comments
Anggita Puspawardani
Anggita Puspawardani on 4 Jun 2020
Here is the line that I changed
SVMModel = fitcsvm(data(train,:),groups(train),'KernelFunction','linear',...
'Standardize',true);
classes = predict(SVMModel,data(test,:));

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Lutfia Nuzula
Lutfia Nuzula on 24 Mar 2020
some problem, but i was run in 2018b. how to solve the error?
  4 Comments

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jasmine bala
jasmine bala on 30 Mar 2021
how to solve the error in matlab 2018?
Group =fitcsvm(svmstruct1.Test_Set_tmp)
  1 Comment
Walter Roberson
Walter Roberson on 30 Mar 2021
Code that used svmstruct is almost always written for the earlier SVM functions that MATLAB does not provide any more. Those functions used numeric arrays, and did not permit table objects.
The newer fitcsvm does not accept being passed just a single parameter: it needs one of
  • table and name of response variable
  • table and "formula" of which variables are related
  • numeric data as first parameter, and information about the labels in the second parameter (not necessarily numeric)

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