目标檢測評價名額解釋（precision, recall, mAP）

Reference:

https://nlp.stanford.edu/IR-book/html/htmledition/evaluation-of-ranked-retrieval-results-1.html

TP, FP, FN, TN

這些名額都源于下表

～	~	預測	預測
～	~	1
實際	1	TP	FN
實際	FP	TN

Precistion Recall

Precision(預測正例正确占所有預測正例的比重) = TP / (TP + FP)

Recall = Ture Positive Rate(分類器識别的正例占) = TP/(TP + FN)

False positive rate = FP / (FP + TN)

False alarm = FP / (FP + TP)

2 / F_1 = 1 / Recall + 1 / Precision

mAP = \int_{1}^{1} P(r) dr

P是修正的Precision

R是Recall