Data Mining

Given a binary classification problem (Class-1 or Class-0), draw a Confusion Matrix showing result counts (fxx) in terms of Predicted and Actual class. Provide calculations for Accuracy and Error Rate, highlighting False Positives (FP) and False Negatives (FN). Given a binary classification problem (Class-1 or Class-0), draw a Confusion Matrix showing result counts (fxx) in terms of Predicted and Actual class. Provide calculations for Accuracy and Error Rate, highlighting False Positives (FP) and False Negatives (FN)