How to show the accuracy on a confusion matrix

Hello!

So I've trained a perceptron with 29 data and I implemented its confusion matrix. Yet I want it to show me the accuracy. So far it only appears as follows:

And this is the code that I used to plot it:

function katataksh= Ask31c (w1,w2,b,x_new,y_new)

W=[w1 w2 b]; %ορίζω τον πίνακα W να παίρνει τις τιμές των w1,w2 και b

New_data=x_new;

y_problepsi_new=sign(New_data(:,1)*W(1,1)+New_data(:,2)*W(1,2)+W(1,3));

katataksh=y_problepsi_new;

apodosh=confusionmat(y_new,katataksh);
accuracy=sum(y_new == katataksh,'all')/numel(katataksh);
confusionchart(apodosh);

end

Note that there's more code that is implemented, but I think it's not necessary to write it here, since I only want to find the accuracy of the confusion matrix.

Thank you in advance!

Answer 1

[Chunru]

You nee to add column and row summaries. Check out the following example from doc.

load fisheriris
X = meas;
Y = species;

Mdl = fitcknn(X,Y,'NumNeighbors',5,'Standardize',1);

predictedY = resubPredict(Mdl);

cm = confusionchart(Y,predictedY);

% The confusion matrix displays the total number of observations in each cell. 
% The rows of the confusion matrix correspond to the true class, and the columns 
% correspond to the predicted class. Diagonal and off-diagonal cells correspond 
% to correctly and incorrectly classified observations, respectively.
%
% By default, confusionchart sorts the classes into their natural order as defined 
% by sort. In this example, the class labels are character vectors, so confusionchart 
% sorts the classes alphabetically. Use sortClasses to sort the classes by a specified
%  order or by the confusion matrix values.
%
% The NormalizedValues property contains the values of the confusion matrix. Display 
% these values using dot notation.

cm.NormalizedValues

ans = 3×3

50 0 0 0 47 3 0 4 46

% Modify the appearance and behavior of the confusion matrix chart by changing property 
% values. Add a title.

cm.Title = 'Iris Flower Classification Using KNN';

% Add column and row summaries.

cm.RowSummary = 'row-normalized';
cm.ColumnSummary = 'column-normalized';