搜索资源列表
Bayesian-algorithm
- 贝叶斯算法一种python实现方式，写法比较朴素，简单易懂-Bayesian algorithm python implementation, written relatively simple, easy to understand
NBC
- 朴素贝叶斯机器学习，用来分类文本，matlab编程，有测试和训练两部分。-Naive Bayesian machine learning to classify text, matlab programming, testing, and training has two parts.
NaiveBayesian
- 使用Python语言写的经典朴素贝叶斯算法的实现，完全能够应对算法设计课程的课程设计的代码需要-Implemented using Python language written in classic Naive Bayes algorithm, fully able to cope with the algorithm design course curriculum design code requires
MachineLearning
- 非常好用的基于QT实现机器学习的朴素贝叶斯算法-Very easy to use machine learning based on QT implement Naive Bayes algorithm
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情色彩分类的程序。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
Main
- 朴素贝叶斯算法的代码实现，能够实现对数据的自相关，互协方差等统计方面特征的数学分析-Code naive Bayes algorithm implementation can be achieved for autocorrelation of the data, mathematical analysis statistical characteristics of the cross-covariance, etc.
NaviveBayesClassify
- Java语言 iris数据集 朴素贝叶斯实现-Iris u6734 u7D20 u8D1D u53F6 u65AF
naive_bayes
- 朴素贝叶斯算法的程序，不知有用否，不记得是从哪里下载到的了(naive bayes algorithm is a machine learning technique, which is used for classification.)
bayes
- 朴素贝叶斯算法解决分类问题（二分类）的matlab代码(Naive Bayes algorithm to solve classification problems (two categories) of matlab code)
NaiveBayesNLP
- 使用weka 运行朴素贝叶斯，去除拉普拉斯平滑(Use weka to run naive bayes, and delete laplace smoothing)
e1071_1.6-8
- klaR包与e1071包都可以做朴素贝叶斯分类，本次试验中，klaR包在使用的时候会出现警告，但不影响预测(Both the klaR package and the e1071 package can be used as a simple Bias classification. In this experiment, the klaR package will be warned when it is used, but it does not affect the prediction.
ipynb
- 机器学习方法之最近邻、朴素贝叶斯、逻辑回归方法的实现与对比(compared with knn\NB\logistics)
垃圾邮件处理 机器学习
- 利用朴素贝叶斯分类器对垃圾信息进行分类处理，得到一个分类器便于分析信息的归属。(Classification of garbage information by naive Byes classifier.)
拼音输入法
- 一个基于朴素贝叶斯算法的拼音输入法。 使用方法见源码。 语言：python
pac_ai-master
- 本文根据美国威斯康星州的乳腺癌诊断数据集，生成一个乳腺癌诊断的SVM分类器，并计算这个分类器的准确率。(import pandas as pd data = pd.read_csv(r'C:\Users\hzjy\Desktop\data.csv'))