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difference.tar
- This a text file include differences bayesian clasification and naive bayes.-This is a text file include differences bayesian clasification and naive bayes.
bayes
- 实现朴素贝叶斯文本分类器，用java实验，还包括readme和训练集-Naive Bayes text classifier to achieve with java experiments, including readme and the training set
57578895BAYES
- 用基于贝叶斯的的方法对文本进行分类主要用于数据挖掘领域-Using the method based on Bayesian text classification is mainly used for data mining
Bayesian
- 朴素贝叶斯模型的源代码，可以用于文本分类-Naive Bayes model source code, can be used for text classification
Bayes-classifier-code
- 朴素贝叶斯分类器程序代码 采用朴素贝叶斯分类器算法，使用C++语言对英文文本进行分类，实现了一个文本分类器功能-Naive Bayesian classifier program code using Bayesian classification algorithm, using C++ language English text classification, to achieve a text classification function
Bayesian
- 朴素贝叶斯模型的源代码，可以用于文本分类Naive Bayes model source code, can be used for text classification-Naive Bayes model source code, can be used for text classification
bayes
- 贝叶斯分类算法源代码，用于对文本文件进行分类-Bayesian classification algorithm source code, used to classify a text file
Naive-Bayes-Text-Classification
- 使用Python实现朴素贝叶斯分类，文件夹中附带数据集。实现了NB算法，并进行5倍交叉验证-Naive Bayes classifier using the Python implementation, the folder with the data set. NB implements the algorithm, and 5-fold cross-validation
Bayes
- 使用贝叶斯对文本进行分类，判断适不适合出去玩-Use Bias to classify the text, the judge is not suitable for play
bys
- 本文主要描述了朴素贝叶斯分类方法，包括模型导出和学习描述。实例部分总结了《machine learning in action》一书中展示的一个该方法用于句子感*彩分类的程序。1 方法概述 学习（参数估计） 实现：朴素贝叶斯下的文本分类-This paper describes the naive Bayesian classification methods, including export and learning descr iptive model. Example
algorithm
- In machine learning, naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive) independence assumptions between the features. Naive Bayes has been studied extensively since the 19
朴素贝叶斯
- 借助朴素贝叶斯算法，针对文本正负面进行判别，并且利用C#进行编程实现(The naive Bayes algorithm is used to judge the positive and negative sides of the text, and the program is implemented by using C#)