Naive Bayes classifier

In this paper , we investigate enhancement of naive Bayes classifier using feature weighting technique .

该文利用特征加权技术来增强朴素贝叶斯分类器。

Compare with the traditional naive bayes classifier , some efficient implementations for our algorithms confirmed the method was correct and feasible .

通过与传统的朴素贝叶斯分类器进行对比实验，验证了该方法的可行性和有效性。

Research on Traffic Pattern Recognition Technology Based on Incremental Naive Bayes Classifier

基于增量式朴素贝叶斯分类方法的电梯交通模式识别方法的研究

The system performance comparing with SVM classifier and Naive Bayes classifier under the same condition .

相同条件下与SVM和NaiveBayes分类器的分类性能比较。

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NaiveBayes分类器。

In the process of single classifier development , this paper modifies naive bayes classifier for its output problem .

在单分类器模型开发过程中，针对朴素贝叶斯分类模型的输出问题进行修正。

Naive Bayes classifier is proved to be one of the simple and effective classifier and be used widely and successfully .

朴素贝叶斯分类算法是一个简单、有效而且在实际使用中很成功的分类算法，其性能可以与其他典型分类算法相媲美，在某些场合还优于其他分类器。

The SD algorithm is a new hybrid of global learning and local learning . Thus it can improve the generalization ability of Naive Bayes classifier .

SD算法是一种组合全局学习和局部学习的算法，因此能够提高NaiveBayes分类器的泛化能力。

Meanwhile Rocchio classifier and Naive Bayes classifier have been constructed in order to compare with the n-gram models on their performance .

同时，为了更加系统、全面地考查N元语言模型的分类性能，文中还进行了N元模型分类器与Rocchio分类器和NaiveBayes分类器的实验对比。

In the software aging prediction , Naive Bayes classifier based on Markov Chain is used . Load balancing algorithm is to plug into software parameter based on original algorithm .

软件老化的预测主要采用基于马尔可夫随机过程的朴素贝叶斯分类器算法，负载均衡算法主要是在原有负载均衡算法的基础之上加入老化参数。

When predicting the aging degree and trend , this paper uses several aging metrics as the input and deploys the Naive Bayes classifier based on Markov Chain .

在预测终端的软件老化趋势与程度的时候，本文采用将多个老化指标作为输入的基于马尔可夫随机过程的朴素贝叶斯分类器模型。

MBN classifier is compared with Naive Bayes classifier and TAN classifier by an experiment . Experimental results show that this model has higher classification accuracy in most data sets .

将该模型算法与朴素贝叶斯及树增广朴素贝叶斯进行实验比较，实验结果表明MBN分类器在多数数据集上具有较高的分类正确率。

Microblogging information classify module using the popular Naive Bayes classifier to classify the message . Naive Bayes classifier include text pre-processing , classify and manual review process .

最后是对微博内容进行分类，微博分类主要是使用朴素贝叶斯分类器来完成的，斯分类器的流程包括文本预处理，分类器分类和人工审核过程。

On the basis of the study of naive Bayes classifier s ( NBC ), a new method & tree augmented naive Bayes classifier is proposed and applied to texture classification .

提出了一种松弛方法，允许类别节点下的相邻子节点之间存在相关关系（有向边），这种方法称为树增强型简单贝叶斯分类器（treeaugmentednaiveBayesclassifier，TAN）。

In the experiment , we use naive bayes classifier and SVM classifier to verify the effectiveness of this method . Thirdly , in text clustering , we also map terms into cloud droplets and condense them into clustering-document-cloud .

实验采用朴素贝叶斯和SVM这两种分类器来验证这种方法的有效性。第三、在文本聚类中，利用云模型理论将特征词映射成聚类词云滴，并将词云滴跃升聚类文档云。

We first analysis the characteristic of HTML documents , then discuss the key technique of automatic text classification , including Vector Space Model , Chinese word segmentation , text feature selection , and implement a multinomial NaiVe Bayes classifier to classify Chinese Web page .

本文首先分析了Web页面的组织特点，对文本自动分类中使用到的向量空间模型、分词、特征选择等关键技术进行了深入的探讨，并实现了一个多项式朴素贝叶斯分类器对中文网页进行分类。

The universal approximation of this model has been proved . The method and process of obtaining the fuzzy if-then rules and conditional probability also has been research based on the former achievement . The probability factor obtaining method based on Fuzzy Naive Bayes Classifier is also discussed .

在前人研究的基础上，讨论了一种从数据集中提取模糊规则if-then及其条件概率的方法和步骤，同时证明了这种系统是一个通用逼近器。

Naive Bayes Text Classifier Based on Word Clusters

基于单词簇的朴素贝叶斯文本分类器

Stump Network text classifier is compared with naive bayes text classifier and TAN ( tree augmented naive bayes ) by an experiment .

将该方法与朴素贝叶斯文本分类器和TAN（treeaugmentednaiveBayes）文本分类器进行实验比较。

To diminish the defect , firstly the words with k-means algorithm are clustered , and word clusters are looked as text feature , then the texts are classified by the naive bayes text classifier .

针对这一问题，首先采用k-means算法对单词进行聚类，将得到的单词簇视为文本特征，再使用朴素贝叶斯分类器进行文本分类。

Naive Bayes ( NB ) classifier has long been considered a core methodology in text categorization mainly due to its simplicity and computational efficiency .

朴素贝叶斯分类器由于其简单性及计算的有效性，一直在文本分类领域中占有很重要的地位。