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The method based on Naive Bayes Model (NBM) is 92%, it’s a higher precision. 基于贝叶斯模型（NBM ）的有指导消歧的开放测试正确率最高可达92 %25 ，取得了比较好的效果。
To train a Naive Bayes model based on the targeted mailing data in the AdventureWorksDW database. 并根据AdventureWorksDW数据库中的目标邮件数据来为Naive Bayes模型定型。
To use a continuous column in a Microsoft Naive Bayes model, you must discretize the data in the column. 若要在Microsoft Naive Bayes模型中使用连续列,必须对列中的数据进行离散化处理。
Naive Bayes model 朴素贝叶斯模型
The following example adds a Naive Bayes mining model to the New Mailing mining structure. 以下示例将Naive Bayes挖掘模型添加到New Mailing挖掘结构中。
The following example uses the Microsoft Naive Bayes algorithm to create a new mining model. 以下示例使用Microsoft Naive Bayes算法创建新的挖掘模型。
For more information, see Microsoft Naive Bayes Algorithm. 有关详细信息,请参阅Microsoft Naive Bayes算法。
A comparison of event models for Naive Bayes text classification. 如果在监督环境下,即文本的类别已知。
Improving the Performance of Naive Bayes: A Hybrid Approach. 通过逼近改进朴素贝叶斯性能。
For more information about how to use the Microsoft Naive Bayes Viewer, see Viewing a Mining Model with the Microsoft Naive Bayes Viewer. 有关如何使用Microsoft Naive Bayes查看器的详细信息,请参阅使用Microsoft Naive Bayes查看器查看挖掘模型。
For more information, see Viewing a Mining Model with the Microsoft Tree Viewer, and Viewing a Mining Model with the Microsoft Naive Bayes Viewer. 有关详细信息,请参阅使用Microsoft树查看器查看挖掘模型和使用Microsoft Naive Bayes查看器查看挖掘模型。
This viewer displays mining models that are built with the Microsoft Naive Bayes algorithm. 该查看器显示使用Microsoft Naive Bayes算法生成的挖掘模型。
To improve efficiency, used naive Bayes classify method to reduce the searching space. 基于效率考虑，利用朴素贝叶斯分类算法减小搜索空间。
Now there are many methods that has been applied to this field, such as SVM, KNN, Naive Bayes, Decision Tree, etc. 目前已经有许多方法应用到该领域。如支持向量机方法(SVM)、K近邻方法(KNN)、朴素贝叶斯方法(Naive Bayes)、决策树方法(Decision Tree)等等。
Presently, naive Bayes algorithm for Email filtering has been accepted widely for its simplicity and plainness. 朴素Bayes邮件过滤算法由于简单、易于理解,已被人们广泛接受,并应用到一些商用邮件系统当中。
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(tree augmented naive bayes)文本分类器进行实验比较。
The Microsoft Naive Bayes algorithm is a classification algorithm that is quick to build and that works well for predictive modeling. Microsoft Naive Bayes算法是一种可快速构建并适合进行预测性建模的分类算法。
Classification algorithms include the Microsoft Decision Trees, Microsoft Naive Bayes, and Microsoft Neural Network algorithms. 分类算法包括Microsoft决策树、Microsoft Naive Bayes和Microsoft神经网络算法。
A junkmail filter is designed and implemented on the basis of naive Bayes filter by tabulating junkmail features in a form of binary system. 以朴素的贝叶斯过滤器为基础,采用二进制表示方法建立垃圾邮件特征表,设计并实现一种垃圾邮件过滤器。
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。