Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

by Foster Provost

Another problem with simple classification accuracy as a metric is that it makes no distinction between false positive and false negative errors. By counting them together, it makes the tacit assumption that both errors are equally important.