correct and incorrect predictors

Dear community members, i am stuck in a problem. I tried to search for the solution but i could not find. I want to get the input data (predictors) of an incorrect predicted class. How can i do that? i am just able to get the incorrect classes in the confusion chart but i need to find the input data of them.
for example lets take this example:
load satdata;
pt = cvpartition(satClass,'holdout',0.3);
predTrain = satData(training(pt),:);
classTrain = satClass(training(pt));
predValid = satData(test(pt),:);
classValid = satClass(test(pt));
knnClassifier = fitcknn(predTrain,classTrain,'Numneighbors',5);
yPred = predict(knnClassifier,predValid);
[c,lbls] = confusionmat(yPred,classValid);
Here i can only see the classes in yPred but i cant see the input data (predictors) of those classes. I hope i am clear to my question.

3 comentarios

Walter Roberson
Walter Roberson el 17 de Sept. de 2022
Unfortunately I cannot tell from here what class(classTrain) is, and so what class(yPred) is.
load fisheriris
pt = cvpartition(species,'holdout',0.3);
predTrain = meas(training(pt),:);
classTrain = species(training(pt));
predValid = meas(test(pt),:);
classValid = species(test(pt));
knnClassifier = fitcknn(predTrain,classTrain,'Numneighbors',5);
yPred = predict(knnClassifier,predValid);
[c,lbls] = confusionmat(yPred,classValid);
Sorry for uploading the wrong code. I have now written a matlab documentation example code for knn classifier.
Saeed Magsi
Saeed Magsi el 17 de Sept. de 2022
Editada: Saeed Magsi el 17 de Sept. de 2022
I have now attached the excel files for yPred and classTrain. If you see in row 23 of yPred it has incorrect prediction of "virginica". Now i want to see its input data (predictors) which i dont know how can this be done? I need your help in this. Thank you once again.

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 Respuesta aceptada

Dinesh
Dinesh el 8 de Jun. de 2023
Hi Saeed!
One simple way to find the incorrect prediction is to iterate over the predictions and store the indices that are not equal in yPred and classValid. Using that indices array we can get the input data predictors for which the predictions were wrong.
indexes = [];
for i = 1:length(yPred)
% Compare values and store index if they don't match
if ~strcmp(yPred{i}, classValid{i})
indexes(end+1) = i;
end
end
data = predValid(indexes, :);
disp(data);
You can do this without for loop also. Use the 'cellfun' fuction
res = cellfun(@isequal, yPred, classValid);
% Find the indexes of non-matching elements
indexes = find(~res);
indexes
data = predValid(indexes, :);
disp(data);
Please refer to the following MATLAB documentation for more details and examples to use cellfun
Hope this helps!
Thank you.

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el 17 de Sept. de 2022

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el 8 de Jun. de 2023

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