correct and incorrect predictors
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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 Comments
Accepted Answer
Dinesh
on 8 Jun 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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