Naive Bayes classifier - Wikipedia
- https://en.wikipedia.org/wiki/Naive_Bayes_classifier
- In , naive Bayes classifiers are a family of simple "" based on applying with strong (naive) assumptions between the features.
- Naive Bayes has been studied extensively since the 1960s. It was introduced (though not under that name) into the community in the early 1960s, and remains a popular (baseline) method for , the problem of judging documents as belonging to one category or the other (such as , sports or politics, etc.) with as the features. With appropriate pre-processing, it is competitive in this domain with more advanced methods including . It also finds application in automatic .
- Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem. training can be done by evaluating a ,:718 which takes , rather than by expensive as used for many other types of classifiers.
- In the and literature, naive Bayes models are known under a variety of names, including simple Bayes and independence Bayes. All these names reference the use of Bayes' theorem in the classifier's decision rule, but naive Bayes is not (necessarily) a method.
1.9. Naive Bayes — scikit-learn 0.20.3 documentation
- https://scikit-learn.org/stable/modules/naive_bayes.html
Machine Learning with Python: Introduction Naive Bayes Classifier
- https://www.python-course.eu/naive_bayes_classifier_introduction.php
贝叶斯、概率分布与机器学习 - 程序员数学之美
- https://mp.weixin.qq.com/s/37D1sq-c9H89YV_mcV8BUQ
- http://www.cnblogs.com/LeftNotEasy/archive/2010/09/27/1837163.html
朴素贝叶斯算法的优缺点 - 机器学习算法与自然语言处理
- https://mp.weixin.qq.com/s/Oxfa6Xvqx5BCO46CMGZB-w
- http://www.cnblogs.com/pinard/p/6069267.html
朴素贝叶斯算法原理小结 - 刘建平Pinard - 博客园
- https://www.cnblogs.com/pinard/p/6069267.html
scikit-learn 朴素贝叶斯类库使用小结 - 刘建平Pinard - 博客园
- https://www.cnblogs.com/pinard/p/6074222.html