• 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Naive Bayes分类器。

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  • Bayes classifier model is a powerful tool for classifying attack types in intrusion detection.

    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。

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  • Experimental results show that Bayes classifier is suitable for the transformer fault diagnosis.

    实验表明提出的选择性贝叶斯分类器适于变压器故障诊断。

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  • Absrtact: An augmented naive Bayes classifier of Bayes classifier family is studied in this paper.

    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。

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  • 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。

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  • This paper presents an efficient automatic categorization system for Chinese journals based on Bayes classifier.

    本文设计了一个有效的基于贝叶斯分类器的中文期刊自动分类系统。

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  • So a new Bayesian model mixed tree augmented Naive Bayes classifier(MTANC) based on the rough set theory is presented.

    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)。

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  • This paper takes Naive Bayes Classifier as an illustration to describe how to construct a prediction module in detail.

    文章以朴素贝叶斯算法为例,详细描述了性能预测模块的构建过程。

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  • TAN(tree augmented Nave Bayes) takes the Nave Bayes classifier and adds edges to it, it is efficient extend of Nave Bayes.

    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。

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  • In this paper, we investigate enhancement to naive Bayes classifier using feature weighting technique based on rough set theory.

    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。

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  • TAN classifier extends the structure of Naive Bayes classifier by adding augmenting arcs that obey certain structural restrictions.

    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。

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  • The algorithm of discrete Bayes classifier is proposed. Then, formulas for estimating classifying error of Bayes classifier are deduced.

    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。

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  • This paper USES the improved K-means (IKM) algorithm to process the missing data and thus improve the precision of the Naive Bayes classifier.

    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。

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  • In designing web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.

    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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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.

    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。

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  • 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.

    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。

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  • Multi-layer classifier Topic search engine Computer education resources Naive Bayes;

    多层分类器; 垂直搜索引擎;计算机教育资源;朴素贝叶斯;

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  • Multi-layer classifier Topic search engine Computer education resources Naive Bayes;

    多层分类器; 垂直搜索引擎;计算机教育资源;朴素贝叶斯;

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