[machine learning theory] true positive, true negative, false positive, false negative concept

True Positive, True Negative, False Positive, False Negative Concept ¹

• True positive-——- The prediction is correct , And it is positive ;
• True negative——- The prediction is correct , And negative ;
• False positive——- Wrong prediction , The forecast is positive ;（ Incorrectly predicted as positive ）
• False negative—— Wrong prediction , Predicted as negative ;（ Incorrectly predicted as negative ）

Ahead True/False Express “ By the way ”, hinder positive/negative Express “ Predicted value ”.

Precision（ Accuracy rate ）

The forecast for 1（predicted The value is 1 The line of ）, Predict the right ratio ;

True positive / (True positive + False positive)

Recall（ Recall rate ）

For the actual is 1（actual The value is 1 The column of ）, Predict the right ratio ;

True positive / (True positive + False negative)

reference

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1. https://blog.csdn.net/Houchaoqun_XMU/article/details/78865985 ︎