When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm’s output matches reality. But according to new research, that tool may not be as reliable as many assume.
Researchers reveal bias in a widely used measure of algorithm performance
