'Handling Imbalanced Class Issues with Matthew’s Correlation Coefficient' machinelearning imbalancedclass
. Before we show the calculation for the MCC, let’s first revisit the concept of a confusion matrix. As you can see in the image below, a confusion matrix has four cells created by combining the predicted values against the real values.
Two of those cells represent correct predictions , and the other represents incorrect predictions .The MCC takes values between -1 and 1. A score of 1 indicates perfect agreement. But how does the MCC compare against other popular metrics for imbalanced classes?is another very popular metric for imbalanced class problems. The F1-score is calculated as:
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