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条件概率
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
条件概率公式: | |
P(A|B) = P(AB)/P(B) | |
P(AB) = P(A)P(B|A) = P(B)P(A|B) | |
P(A|B) = P(A)P(B|A)/P(B) | |
全概率公式: | |
P(A) = P(B1)P(A|B1) + P(B2)P(A|B2) + ... // B1,B2...是全集 | |
参考: | |
http://baike.baidu.com/view/965891.htm | |
问题: | |
得病概率为x,假阳性概率为y,假阴性概率为z。则检查出了阳性,得病概率是? | |
事件定义: | |
D: 得病 // Disease | |
C: 检查出阳性 // Check out | |
已知: | |
得病概率为x,P(D) = x, P(!D) = 1 - x | |
假阳性概率为y,即没有得病但检查出阳性概率 P(C|!D) = y, P(!C|!D) = 1 - y | |
假阴性概率为z,即得病检查但出阴性概率 P(!C|D) = z, P(C|D) = 1 - z | |
求解: | |
检查出了阳性,得病概率 P(D|C) = ? | |
解答: | |
P(D|C) = P(D)P(C|D) / P(C) = P(D)P(C|D) / ( P(D)P(C|D) + P(!D)P(C|!D) ) | |
= x * (1-z) / ( x * (1-z) + (1-x) * y ) | |
""" | |
import sys | |
if len(sys.argv) != 4: | |
print("Usage: python %s <Disease Probability> <False Positive Probability> <False Negative Probability>" | |
% sys.argv[0]) | |
sys.exit(-1) | |
x = float(sys.argv[1]) | |
y = float(sys.argv[2]) | |
z = float(sys.argv[3]) | |
print(x * (1 - z) / (x * (1 - z) + (1 - x) * y)) | |
# 几个典型结果 | |
# 0.01 0 0 => 1 | |
# 0.01 0 0.5 => 1 | |
# 0.01 0.01 0.01 => 0.5 | |
# | |
# 0.0001 0 0 => 1 | |
# 0.0001 0.02 0 => 0.00497561946462 | |
# 0.0001 0.01 0 => 0.00990197049213 | |
# 0.0001 0.01 0.01 => 0.00980392156863 |
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