Focusing on the characteristics in the course of probability theory and mathematical statistics and adhereing to the unity of knowledge transmission and value guidance,two teaching cases were presented aiming at the issues of brushing fraud and machine learning classification based on the Bayes formula.In the first case,the brushing fraud problem is refined into a universal teaching case of Bayes formula by steps such as problem description,modeling,analysis,and problem extension.In the second case,classification problem in machine learning is refined into an applied teaching case by introducing the definition of conditional independence and naive Bayesian classifiers.
关键词
概率论/贝叶斯公式/教学案例/朴素贝叶斯
Key words
probability theory/Bayes formula/teaching case/naive Bayes
维普
万方数据