对贝叶斯分类模型的准确性及其主要特点进行了分析。
The accuracy and the main features of Bayesian classification models are analyzed.
贝叶斯分类模型是入侵检测中用于攻击类型分类的有力工具。
Bayes classifier model is a powerful tool for classifying attack types in intrusion detection.
本文提出了一种结合贝叶斯分类的水平集方法用于医学图像分割。
In this paper, a level set segmentation algorithm based on Bayesian classification for medical image segmentation was proposed.
结合胶州湾实际调查数据，探讨了贝叶斯分类方法在该领域的应用。
In this paper, the observed data in the Jiaozhou Bay are used to explore the application of Bayes classification method to the research field.
讨论了离散贝叶斯分类算法之后，推导了离散贝叶斯分类器的分类误差估算公式。
The algorithm of discrete Bayes classifier is proposed. Then, formulas for estimating classifying error of Bayes classifier are deduced.
它主要有两种分类方法：一种为朴素贝叶斯分类，另一种为贝叶斯信念网络分类。
It is mainly of two kinds, Naive Bayesian Classification and Bayesian Belief Network Classification.
因此，提出了一种基于粗糙集理论的混合树增广朴素贝叶斯分类模型（MTANC）。
So a new Bayesian model mixed tree augmented Naive Bayes classifier(MTANC) based on the rough set theory is presented.
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。
The experiment of Naive Bayes classification indicates that this method can effectively improve classification precision of Chinese texts.
本文利用改进的K -均值算法对缺失数据进行处理，提高了朴素贝叶斯分类的精确度。
This paper USES the improved K-means (IKM) algorithm to process the missing data and thus improve the precision of the Naive Bayes classifier.
对隐含时间表达的识别，即汉语情态的分析，采用贝叶斯分类法进行动词分类和情态分类。
For implicit temporal expression recognition, witch is also called as Chinese situation analysis. The Bayes classification is used for Chinese verb classification.
在垃圾邮件分类和朴素贝叶斯算法研究的基础上，提出了基于用户知识的贝叶斯分类算法。
An user knowledge based na? Ve bayes classifier was proposed in order to conquer the problem that most of the E-mail is unstructured and need users decoding.
对朴素贝叶斯分类算法进行拓展，使其应用到多关系数据分类领域，并引入了用户指导的概念。
We extended the Naive Bayesian Classifier, applied it in the relational classification filed, and introduced the concept of user's guidance.
将聚类算法引入到朴素贝叶斯分类研究中，提出一种基于聚类的朴素贝叶斯分类算法(CNBC)。
A Naive Bayesian classification based on clustering principle (CNBC) by introducing clustering algorithm into Naive Bayesian classification.
对数据挖掘中的贝叶斯分类技术进行了讨论，重点分析了朴素贝叶斯分类技术的基本原理和工作过程。
The Bayesian classification technology in Data mining was discussed, and the research was emphasized on the basic principle and the work procedure of the Naive Bayesian classification technology.
着重介绍了采用明文特征和朴素贝叶斯分类相结合的方法，对加密的以及未加密的P 2 P流量进行识别。
It was the highlights of the paper that the method combined the explicit features and naive bayes classifier together to identify both of the encrypted and not encrypted P2P traffic.
通过分析贝叶斯定理的变形公式和属性相关性度量，提出一种基于强属性限定的贝叶斯分类模型SANBC。
On the basis of analyzing a variant of Bayes theorem and the evaluation of condition attribute with correlation, SANBC is proposed.
朴素贝叶斯分类是一种简单而高效的分类模型，然而条件独立性假设在现实中很少出现，致使其性能有所下降。
Naive Bayes classification is a kind of simple and effective classification model. However, the performance of this model may be poor due to the assumption on the condition independence.
系统采用黑白名单过滤、邮件特征过滤和贝叶斯分类相结合的三层过滤技术，并通过用户反馈机制降低误报率。
The filtering system was built up with multi-layer filtering technology as blacklist technology, characteristic filtering, Naive Bayesian, and user feedback mechanism.
文中针对该算法这两个最主要的缺陷，提出增量学习概念，引入损失幅度参数，改进和完善朴素贝叶斯分类算法。
Then in allusion to these two important factors, a concept of incremental learning and a loss extent parameter are put forward in this paper, and Native Bayesian Classification.
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.
现有的分类预测的方法有许多种，常见的有决策树算法(C4.5)、贝叶斯分类算法、BP算法与支持向量机等。
There are many classification methods to forecast such as decision tree algorithm (C4.5), Bayes algorithm, BP algorithm and SVM.
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。
This paper focuses on privacy preserving classification, and presents a privacy preserving Naive Bayes classification approach based on data randomization and feature reconstruction.
并且与图像分类中统计方法的经典算法贝叶斯分类方法做了比较，结果发现，神经网络分类方法的分类效果要优于贝叶斯方法。
Comparing with Bayes method-the classical algorithm, we conclude that the neural network is better than Bayes method. This paper gives all the procedures of SAR image classification.
为了解决该方法存在的训练数据集问题，本文改进了现有的贝叶斯分类算法，提出了利用未标记数据提高贝叶斯分类器性能的方法。
In order to solve the problem existing in training data sets, present Bayes algorithm is im - proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.
研究了人脸检测的贝叶斯特征判别法，该方法包括三个部分：原始图像的特征判别分析、人脸区和其它区的统计建模以及贝叶斯分类器。
The main idea of which consists of three parts: the discriminating feature analysis of the images, the statistical modeling of face and non-face classes, and the Bayes classifier for face detection.
提出了一种基于贝叶斯分类与机读词典的多义词排歧方法，通过小规模语料库的训练和歧义词在机读词典中的语义定义来完成歧义的消除。
A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.
针对模式分类中高置信度的先验概率分布难以设定的问题，提出了一种新的应用贝叶斯分析进行模式分类的方法。
To overcome the hardship of enacting the pre-probability distribution with high certainty factor, this paper proposes one novel way of applying Bayes analysis to classify pattern.
基于贝叶斯模型的文档分类具有简单、直观、性能稳定的优点，但面对复杂的文档分类问题，仍然存在许多急待解决的问题。
Although text classification with Bayesian classifier is simpler, intuitionistic and stable in performance, they still face with some significant problems in some complex text classification tasks.
提出并实现了一个基于贝叶斯的冬态树木自动分类的系统。
In the paper it puts forward and implements a hibernal tree automatic classification system based on Bayes.
基于粗糙集、模糊集和贝叶斯最优分类器，提出一种变压器绝缘故障诊断与维护的综合决策模型。
Based on Bayesian optimal classifier, combining with rough set and fuzzy set, a new transformer fault diagnosis and maintenance mode is presented in the paper.
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