how can i use struct to "for" when i use predictFcn

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영훈 정 2023-4-5

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1941759-how-can-i-use-struct-to-for-when-i-use-predictfcn

编辑： Stephen23 2023-4-5

采纳的回答： Luca Ferro

在 MATLAB Online 中打开

i want to predict by use "for"

i have 15 number of sturct

how can i use "for"..?

for modelname = [Tree Linear InteractionsLinear RobustLinear StepwiseLinear LinearSVM QuadraticSVM CubicSVM FinegaussianSVM MediumGaussianSVM CoarseFaussianSVM RationalQuadraticGPR SquaredExponentialGPR Matern52GPR ExponentialGPR]
    var1=data_1(:);
    var2=data_2(:);
    insertdata=table(var1,var2);
    predictdata=modelname.predictFcn(insertdata)
end

this code didn't work..

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Answer 1

Luca Ferro 2023-4-5

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https://ww2.mathworks.cn/matlabcentral/answers/1941759-how-can-i-use-struct-to-for-when-i-use-predictfcn#answer_1209594

编辑：Luca Ferro 2023-4-5

You should have all the model names in an array, then loop using a proper index and eval the expression.

modelNames=["Tree", "Linear", "InteractionsLinear", "RobustLinear", "StepwiseLinear", "LinearSVM", "QuadraticSVM", "CubicSVM", "FinegaussianSVM" ,"MediumGaussianSVM","CoarseFaussianSVM","RationalQuadraticGPR" ,"SquaredExponentialGPR" ,"Matern52GPR","ExponentialGPR"];

var2=data_2(:);

insertdata=table(var1,var2);

for nn=1:size(modelNames,2)

predictdata=eval(strcat(modelNames(nn),'.predictFcn(insertdata)'));

end

Probably there is a better way using dynamic field naming for structs but i could not implement it in a short time.

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Answer 2

Stephen23 2023-4-5

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1941759-how-can-i-use-struct-to-for-when-i-use-predictfcn#answer_1209644

编辑：Stephen23 2023-4-5

在 MATLAB Online 中打开

"i have 15 number of sturct"

And that is a problem which is best solved by putting them into one array (which they clearly should have been right from the start). It is best to avoid slow, complex, inefficient, evil EVAL.

For example, assuming that all of those structures are scalar with the same fieldnames:

S = [Tree,Linear,InteractionsLinear,RobustLinear,StepwiseLinear,LinearSVM,QuadraticSVM,CubicSVM,FinegaussianSVM,MediumGaussianSVM,CoarseFaussianSVM,RationalQuadraticGPR,SquaredExponentialGPR,Matern52GPR,ExponentialGPR];
for k = 1:numel(S)
    ..
    S(k).predictFcn(insertdata)
    ..
end