Listing 1 shows what a simple document classifier might look like.
清单1说明了一个简单的文档分类程序可能是什么样子。
The first approach is a simple Map-Reduce-enabled Naive Bayes classifier.
第一种方法是使用简单的支持Map - Reduce的Naive Bayes分类器。
Naive Bayes classifier is a simple and effective classification method based on probability theory, but its attribute independence assumption is often violated in the real world.
朴素贝叶斯分类器是一种简单而有效的概率分类方法，然而其属性独立性假设在现实世界中多数不能成立。
When building a binary classifier, many practitioners immediately jump to logistic regression because it's simple.
当构建一个二元分类器时，很多实践者会立即跳转到逻辑回归，因为它很简单。
Naive Bayes classifier is a simple and effective classification method. Classifying based on Bayes Technology has got more and more attentions in the field of data mining.
朴素贝叶斯分类器是一种简单而高效的分类器，基于朴素贝叶斯技术的分类是当前数据挖掘领域的一个研究热点。
Bayesian classifier is excellent at simple network structure and extending easily. It is effective for classifying maize disease and it can use for reference for the image recognition re...
贝叶斯分类器具有网络结构简单、易于扩展等特点，对玉米叶部病害的分类识别效果较好，也为其它作物病害图像识别的研究提供了借鉴。
Naive Bayes classifier is a simple and effective classification method, but its attribute independence assumption makes it unable to express the dependence among attributes in the real world.
朴素贝叶斯分类器是一种简单而高效的分类器，但是其属性独立性假设限制了对实际数据的应用。
Absrtact: Naive Bayesian classifier is a simple and effective classifier, but its conditional independence assumption makes it unable to express the dependence among features.
摘要：朴素贝叶斯分类器是一种简单而高效的分类器，但它的条件独立性假设使其无法表示属性问的依赖关系。
Study on classifier began comparingly late, and been ignored for its simple form during the period of formal grammar.
量词的研究起步较晚，由于其语法形式较简单，在形式语法占主导的地位的时期，也一直不被重视。
SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.
SFAM是一个改进版神经网络分离器，是模糊ARTMAP的简化和快速版本。对于相同的输入FAM和SFAM具有相同的输出。
SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.
SFAM是一个改进版神经网络分离器，是模糊ARTMAP的简化和快速版本。对于相同的输入FAM和SFAM具有相同的输出。
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