Understanding False Positives in Automated Text Classification Systems
Automated text classification can sort emails, label support tickets, flag spam, and group documents in seconds. Still, a classifier can make mistakes, even when its accuracy score looks good. One of the most common mistakes is a false positive. Understanding why false positives happen helps you judge a model more fairly and decide when its
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