【无标题】

机器学习第五次作业

6.1

由第一次检测:
P(⊕∣cancer)P(cancer)=0.0078P(⊕∣cancer)P(cancer)=0.0078P(⊕∣cancer)P(cancer)=0.0078
P(⊕∣¬cancer)P(¬cancer)=0.0298P(⊕∣\neg cancer)P(\neg cancer)=0.0298P(⊕∣¬cancer)P(¬cancer)=0.0298、

将第一次检测结果作为新的先验概率,归一化得到:
P(cancer∣⊕)=0.0078/0.0376=0.2074P(cancer∣⊕)=0.0078/0.0376=0.2074P(cancer∣⊕)=0.0078/0.0376=0.2074
P(¬cancer∣⊕)=0.0298/0.0376=0.7926P(\neg cancer∣⊕)=0.0298/0.0376=0.7926P(¬cancer∣⊕)=0.0298/0.0376=0.7926

第二次检测的后验概率:
P(cancer∣⊕,⊕)=P(⊕∣cancer)∗P(cancer∣⊕)=.098∗0.2074=0.2033P(cancer∣⊕,⊕)=P(⊕∣cancer)*P(cancer∣⊕)=.098*0.2074=0.2033P(cancer∣⊕,⊕)=P(⊕∣cancer)∗P(cancer∣⊕)=.098∗0.2074=0.2033
P(¬cancer∣⊕,⊕)=P(⊕∣¬cancer)∗P(¬cancer∣⊕)=0.03∗0.7926=0.0238P(\neg cancer∣⊕,⊕)=P(⊕∣\neg cancer)*P(\neg cancer∣⊕)=0.03*0.7926=0.0238P(¬cancer∣⊕,⊕)=P(⊕∣¬cancer)∗P(¬cancer∣⊕)=0.03∗0.7926=0.0238

归一化得:
P(cancer∣⊕,⊕)=0.2033/0.2271=0.8952P(cancer∣⊕,⊕)=0.2033/0.2271=0.8952P(cancer∣⊕,⊕)=0.2033/0.2271=0.8952
P(¬cancer∣⊕,⊕)=0.0238/0.2271=0.1048P(\neg cancer∣⊕,⊕)=0.0238/0.2271=0.1048P(¬cancer∣⊕,⊕)=0.0238/0.2271=0.1048

6.2

根据贝叶斯公式:
P(cancer∣⊕)=P(⊕∣cancer)∗P(cancer)P(⊕)=P(⊕∣cancer)∗P(cancer)P(⊕∣cancer)P(cancer)+P(⊕∣¬cancer)P(¬cancer)=1P(⊕∣cancer)P(cancer)+P(⊕∣¬cancer)P(¬cancer)P(⊕∣cancer)∗P(cancer)=11+P(⊕∣¬cancer)P(¬cancer)P(⊕∣cancer)∗P(cancer)P(cancer∣⊕)=\frac{P(⊕∣cancer)*P(cancer)}{P(⊕)}\\=\frac{P(⊕∣cancer)*P(cancer)}{P(⊕∣cancer)P(cancer)+P(⊕∣\neg cancer)P(\neg cancer)}\\=\frac{1}{\frac{P(⊕∣cancer)P(cancer)+P(⊕∣\neg cancer)P(\neg cancer)}{P(⊕∣cancer)*P(cancer)}}\\=\frac{1}{1+\frac{P(⊕∣\neg cancer)P(\neg cancer)}{P(⊕∣cancer)*P(cancer)}}P(cancer∣⊕)=P(⊕)P(⊕∣cancer)∗P(cancer)=P(⊕∣cancer)P(cancer)+P(⊕∣¬cancer)P(¬cancer)P(⊕∣cancer)∗P(cancer)=P(⊕∣cancer)∗P(cancer)P(⊕∣cancer)P(cancer)+P(⊕∣¬cancer)P(¬cancer)1=1+P(⊕∣cancer)∗P(cancer)P(⊕∣¬cancer)P(¬cancer)1

而将P(⊕∣cancer)P(cancer)P(⊕∣cancer)P(cancer)P(⊕∣cancer)P(cancer)和P(⊕∣¬cancer)P(¬cancer)P(⊕∣\neg cancer)P(\neg cancer)P(⊕∣¬cancer)P(¬cancer) 归一化,得到的正是P(⊕∣cancer)P(cancer)P(⊕)\frac{P(⊕∣cancer)P(cancer)}{P(⊕)}P(⊕)P(⊕∣cancer)P(cancer)和P(⊕∣¬cancer)P(¬cancer)P(⊕)\frac{P(⊕∣\neg cancer)P(\neg cancer)}{P(⊕)}P(⊕)P(⊕∣¬cancer)P(¬cancer),而前者正是P(cancer∣⊕)P(cancer∣⊕)P(cancer∣⊕),因此这样是正确的

相关推荐
flyinsono2 分钟前
宠物医疗数字化升级,选对工具少走弯路
人工智能·宠物
VivienneLuo3 分钟前
3. 联邦图学习-《Federated Graph Neural Networks: Overview, Techniques and Challenges》
人工智能·gnn·联邦学习
吴声子夜歌4 分钟前
ApacheCommons——commons-text(模板替换与文本算法)
java·开发语言·算法·apache
Sky1987star7 分钟前
产品资料更新后,怎样让 AI 内容与客服同步生效?
大数据·人工智能
flyinsono10 分钟前
单体宠物诊所数字化转型,选对管理系统少走弯路
大数据·人工智能·宠物
cxr82810 分钟前
AI时代科学研究思维框架的适应性分析与检查清单构建
大数据·人工智能·认知框架
新知图书13 分钟前
第8章 多智能体协同
人工智能·设计模式·智能体
古养摩登原始人26 分钟前
脑机接口合规最新发展:从政策到实践,构建安全可控的技术生态
人工智能·安全
JSCircuit26 分钟前
高校材料工艺实验室采购真空甲酸炉的深度分析与选型指南
人工智能·经验分享·ai写作
阿童木写作28 分钟前
跨境电商翻译工具推荐:批量图片翻译+视频字幕实时翻译
人工智能·python·音视频