Naive Bayes Classification的意思|示意
朴素贝叶斯分类
Naive Bayes Classification的网络常见释义
朴素贝叶斯分类 朴素贝叶斯分类(Naive Bayes Classification) 朴素贝叶斯分类器是一类简单概率分类器，它基于把贝叶斯定理运用在特征之间关系的强独立性假设上。
叶斯分类 文献摘要信息 当前位置：正文 原文获取相似文献参考文献引证文献馆藏信息 选择性加权朴素贝叶斯分类方法的探讨 朴素贝叶斯分类(Naive Bayes Classification,NBC)方法是简单的贝叶斯分类方法,在众多分类方法和理论中,它具有计算效率高、精确度高、理论基础坚实等特点,
Naive Bayes Classification相关例句
The experiment of Naive Bayes classification indicates that this method can effectively improve classification precision of Chinese texts.
基于朴素贝叶斯分类方法的实验表明，提出的方法能够有效提高中文文本的分类准确率。
Naive Bayes algorithm is a simple and effective classification algorithm. However, its classification performance is affected by its conditional attribute independence assumption.
朴素贝叶斯算法是一种简单而高效的分类算法，但是它的条件独立性假设影响了其分类性能。
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。
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。
This paper focuses on privacy preserving classification, and presents a privacy preserving Naive Bayes classification approach based on data randomization and feature reconstruction.
围绕着分类挖掘中的隐私保护问题展开研究，给出了一种基于数据处理和特征重构的朴素贝叶斯分类中的隐私保护方法。
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。