Matthews Correlation Coefficient
Matthews Correlation Coefficient (MCC) is a statistical measure used in machine learning and binary classification to evaluate the quality of predictions. It takes into account true and false positives and negatives, providing a balanced score that is robust to class imbalance. MCC ranges from -1 (perfect disagreement) to +1 (perfect agreement), with 0 indicating random prediction.
Developers should learn and use MCC when working on binary classification problems, especially with imbalanced datasets where metrics like accuracy can be misleading. It is particularly useful in fields like medical diagnosis, fraud detection, and spam filtering, where false positives and negatives have significant consequences. MCC provides a single informative value that summarizes classifier performance comprehensively.