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.
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.
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.
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.
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.
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.
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.
用支持向量机和贝叶斯两种方法对蛋白质四级结构进行分类研究。
The quaternary structure was classified using support vector machine method and Bayes method.
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.
掌握利用贝叶斯公式进行设计分类器的方法。
Master the use of Bayesian classifier design formula method.
运用经典的贝叶斯决策方法将预抓取物体进行基本的三类抓、握、捏抓取模式分类。
The classical Bayes method is used in the classification of pre-grasp of multiple fingers based on three patterns which are grasping, holding and pinching.
本文提出了一种基于贝叶斯方法的电子邮件分类器，讨论了其基本思想，给出了实现的系统结构。
This paper proposes a Bayesian method based E-mail classifier, discusses the idea and gives the system structure.
贝叶斯方法在文本分类中具有较高的准确率。
Bayes method has the higher rate of accuracy while in the text classifying.
目前遥感影像分类的常用模型和算法有统计学方法、神经网络、贝叶斯等。
Current remote sensing image classification models and algorithms commonly used statistical methods, neural networks, Bayesian and so on.
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.
贝叶斯方法是那些明确地在分类和回归问题中应用贝叶斯定理的算法。
Bayesian methods are those that are explicitly apply Bayes' Theorem for problems such as classification and regression.
主要介绍了贝叶斯网络分类器中的TAN分类器的模型、构造方法及分类方法。
This paper mainly introduces the TAN classifier model, its building method and class method.
研究表明依据专家知识自动提取方法能够有效解决现有贝叶斯专家系统分类器中存在的瓶颈问题。
According to the knowledge auto-extraction method developed in this study, the bottleneck of knowledge acquirement in Bayesian expert system classifier could be well solved.
贝叶斯网络分类器是数据挖掘与知识发现领域研究的主要方法之一。
Bayesian network classifier is one of the main research methods in data mining and KDD domain.
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.
方法收集343种传染病症状、体征数据，运用贝叶斯算法建立分类模型。
Methods The data on 343 kinds of infectious disease symptoms, signs were collected and Bayesian classification model was constructed.
实验结果表明，属性依赖贝叶斯方法有较好的分类性能。
The experimental results show that Bayes attributes-depending classification has a better performance of classification.
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.
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.
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