I’m currently going through past paper questions and was wondering if I could get some help answering this one?
‘Consider a classification model which is applied to a set of records, of which 100 records belong to class A (the positive class) and 900 records to class B. The model correctly predicts the class of 20 records in A and incorrectly predicts the class of 100 records in class B. Calculate the values of the confusion matrix, the accuracy, and the error rate.’
My current idea is that the 20 correctly predicted values fall into TP and the 100 values that were supposed to be in class A but were classified as class B fall into FN?
Any recommendations or ideas are much appreciated, thanks.