摘要:6.7Modeling Linguistic Patterns 建模语言模式 Classifiers can help us to understand the linguistic patterns that occur in natural language, by allowing us to create explicit models that capture those patterns. Typically, these models are using supervised classification techniques, but it is also possible . 阅读全文
posted @ 2011-09-03 18:27 牛皮糖NewPtone 阅读 (751) 评论 (0) 编辑
摘要:6.6Maximum Entropy Classifiers最大熵分类器 The Maximum Entropy classifier uses a model that is very similar to the model employed by the naive Bayes classifier. But rather than using probabilities to set the model's parameters, it uses search techniques to find a set of parameters that will maximize t 阅读全文
posted @ 2011-09-03 18:25 牛皮糖NewPtone 阅读 (5319) 评论 (0) 编辑
摘要:6.5Naive Bayes Classifiers朴素贝叶斯分类器 In naive Bayes classifiers, every feature gets a say in determining which label should be assigned to a given input value. To choose a label for an input value, the naive Bayes classifier begins by calculating the prior probability(先验概率) of each label, which is de. 阅读全文
posted @ 2011-09-03 18:21 牛皮糖NewPtone 阅读 (3887) 评论 (0) 编辑
摘要:6.4Decision Trees 决策树 In the next three sections, we'll take a closer look at three machine learning methods that can be used to automatically build classification models: decision trees, naive Bayes classifiers, and Maximum Entropy classifiers. As we've seen, it's possible to treat thes 阅读全文
posted @ 2011-09-03 18:13 牛皮糖NewPtone 阅读 (3327) 评论 (0) 编辑