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Carolyne · 2024年04月21日

correctly predict

NO.PZ2023040502000081

问题如下:

Exhibit 1 provides results from a sample of loans from the ALPHA model that compared expected and actual defaults over the past 12 months.


While reviewing the model documentation, Lovell confirms that the model was able to correctly predict a default in 5,290 instances of the model prediction dataset after the completed data wrangling.

Based on the results provided for the ALPHA model (Exhibit 1) and its associated documentation, the precision of the model is closest to:

选项:

A.

75.4%

B.

85.5%

C.

95.1%

解释:

C is correct. Precision (P) = TP/(TP + FP), where

TP = True positive = 5,290

FP = False positive = Type 1 error = 273

FN = False negative = Type 2 error = 894

P = 5,290/(5,290 + 273) = 5,290/5,563 = 95.1%.

A is incorrect. The calculation incorrectly uses the total number of predictions in the denominator: 5,290/7,018 = 75.4%.

B is incorrect. The calculation uses the correct equation but incorrectly treats a Type 2 error as a false positive and a Type 1 error as a false negative:

P = TP/(TP + FP) = 5,290/(5,290 + 894) = 5,290/6,184 = 85.5%.

请问 correctly predict 不包括FN吗 why

1 个答案

王园圆_品职助教 · 2024年04月22日

同学你好,type I error这个知识点是一级的数量而不是equity 哦,品职不同老师负责的学科是不同的,助教这里没有办法回答你数量的题目哦。同学重新开一个问题,选对学科提问吧,这样才能更好的得到准确的回答哦!