Confusion Matrix without Confused

As we know, the output for classification problem is consists from two target variables, either 0 or 1; Yes or No; Positive or Negative; etc. and our model is trying to classify whether a specific data is 0 or 1; Yes or No; etc. The columns are representing the True Class, which means true or real label for the specific data. The rows are representing the Predicted Class, which means the prediction results derived from our model for the specific use case. True Positive (TP) TP is simply the count of data where the Predicted value is Positive and True value is Positive too. True Negative (TN) TN is simply the count of data where the Predicted value is Negative and True value is Negative too.