构造了保持隐私的朴素贝叶斯分类器。
We construct the privacy preserving Naive Bayesian Classifier.
该文利用特征加权技术来增强朴素贝叶斯分类器。
In this paper, we investigate enhancement of naive Bayes classifier using feature weighting technique.
论文研究了三种朴素贝叶斯分类器信用评估模型的精度。
This paper investigates the credit scoring accuracy of three naive Bayesian classifier models.
本文基于粗糙集理论探索特征加权技术对朴素贝叶斯分类器的改进。
In this paper, we investigate enhancement to naive Bayes classifier using feature weighting technique based on rough set theory.
摘要：文中研究贝叶斯分类器家族中的一种扩展朴素贝叶斯分类器。
Absrtact: An augmented naive Bayes classifier of Bayes classifier family is studied in this paper.
就算该假设不成立，朴素贝叶斯分类器在实践中仍然有着不俗的表现。
And even if the NB assumption doesn't hold, a NB classifier still often does a great job in practice.
此种扩展朴素贝叶斯分类器满足两个条件：一是类结点是所有属性的父结点；
This classifier is defined by the following two conditions-one is that each attribute has the class attribute as parent;
TAN分类器按照一定的结构限制，通过添加扩展弧的方式扩展朴素贝叶斯分类器的结构。
TAN classifier extends the structure of Naive Bayes classifier by adding augmenting arcs that obey certain structural restrictions.
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。
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。
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.
在文本分类器的设计中，用传统信息检索的空间向量模型改进了朴素贝叶斯分类器，提高了它的分类精度。
In designing web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.
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。
Absrtact: Naive Bayesian classifier is a simple and effective classifier, but its conditional independence assumption makes it unable to express the dependence among features.
树扩展型朴素贝叶斯（TAN）分类器放松了朴素贝叶斯的属性独立性假设，是对朴素贝叶斯分类器的有效改进。
TAN(tree augmented Nave Bayes) takes the Nave Bayes classifier and adds edges to it, it is efficient extend of Nave Bayes.
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。
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.
倘若条件独立性假设确实满足，朴素贝叶斯分类器将会比判别模型，譬如逻辑回归收敛得更快，因此你只需要更少的训练数据。
If the NB conditional independence assumption actually holds, a Naive Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data.
倘若条件独立性假设确实满足，朴素贝叶斯分类器将会比判别模型，譬如逻辑回归收敛得更快，因此你只需要更少的训练数据。
If the NB conditional independence assumption actually holds, a Naive Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data.
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