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Classification threshold: Difference between revisions
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{{see also|Machine learning terms}} | {{see also|Machine learning terms}} | ||
==Introduction== | ==Introduction== | ||
In [[machine learning]], [[classification]] is a task where the goal is to assign an [[input]] [[data point]] to one of several predefined categories or [[ | In [[machine learning]], [[classification]] is a task where the goal is to assign an [[input]] [[data point]] to one of several predefined categories or [[class]]es. One critical decision that must be made while performing classification is setting the [[classification threshold]]; this determines when the [[algorithm]] assigns a data point to one [[class]] or another. | ||
==Classification Threshold in Binary Classification== | ==Classification Threshold in Binary Classification== | ||
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Sometimes, however, the computer can't tell if a number is from a dog or cat and needs help deciding. That's where classification thresholds come into play; we can decide on an outcome by setting a number. | Sometimes, however, the computer can't tell if a number is from a dog or cat and needs help deciding. That's where classification thresholds come into play; we can decide on an outcome by setting a number. | ||
[[Category:Terms]] [[Category:Machine learning terms]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:not updated]] | ||