Answer:
ExplanYou can create a confusion matrix using only ones and zeros by representing each actual and predicted class as a binary value.
For example, if you have two classes, "positive" and "negative", you can represent the "positive" class as 1 and the "negative" class as 0.
In this case, you have 3 classes and you can use 1,0 and -1 as representation.
The confusion matrix using only ones and zeros would look like this:
Actual Class 1 Actual Class 2 Actual Class 3
Predicted Class 1 -1 0 0
Predicted Class 2 0 -1 4
Predicted Class 3 0 4 -1
The values in the matrix represent the number of instances that were predicted to be in a certain class and actually belong to another class.
For example, the value -3 in the top left corner represents the number of instances that were predicted to be in class 1 and actually belong to class 1.
Note that in general, when working with confusion matrix, negative values are not common.ation: