搜索资源列表
bayes
- 使用朴素贝叶斯对垃圾邮件进行分类，附带数据(For spam classification using Naive Bayesian, supplementary data)
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#)
NativeBayes
- 朴素贝叶斯垃圾邮件分类器，好歹哦后期维护阿里斯顿啊两千万(Naive Bayes spam classifier)
GAIN
- 决策树，熵，往后我好后期往后完全合乎请问后期往后大(Naive Bayes spam classifier, somehow Oh, later maintenance ARISTON ah twenty million)
82115127
- this source about naive bayes program and nice program div hr di()
Naive Bayes Classifier in C# - Copy
- The code above does a couple things. First it takes in two lists of strings (SetA being Spam and SetB being Ham). These lists would be individual words from the messages (although you can do phrases, word pairs, etc.).
朴素贝叶斯
- 基于对朴素贝叶斯的理解，用java语言实现的简单的朴素贝叶斯过程(Java implementation of naive Bayes)
codeFramework
- matlab 的naivebayes程序(This is a matlab code naive bayes)
Url
- 利用朴素贝叶斯BS实现从HTTP数据流中识别出用户基于浏览器访问的URL(Using the naive Bayes BS to realize the user based browser access based URL from the HTTP data stream)
javamail
- 基于朴素贝叶斯的一个具有图形界面的垃圾邮件过滤系统(A spam filtering system based on Naive Bayes)
朴素贝叶斯算法
- 此处python实现机器学习朴素贝叶斯算法(Here Python implements the naive Bayes algorithm for machine learning)
人工智能：人工智能选股之朴素贝叶斯模型
- 本报告对 朴素贝叶斯模型及线性判别分析、二次判别分析 进行系统测试 “生成模型”是机器学习中监督学习方法的一类。与“判别模型”学习决 策函数和条件概率不同，生成模型主要学习的是联合概率分布??(??,??)。本 文中，我们从朴素贝叶斯算法入手，分析比较了几种常见的生成模型（包 括线性判别分析和二次判别分析）应用于多因子选股的异同，希望对本领 域的投资者产生有实用意义的参考价值。(This report gives a systematic test of naive Bayesian
py_ex
- 利用朴素贝叶斯理论，将垃圾邮件的做分类，使用python代码，内涵邮件数据(Naive Bayes theory is used to classify spam, using Python code, and content mail data.)
nb
- 朴素贝叶斯分类分为两步： ① 计算特征项和所属类别之间的概率; ② 判断文本dj是否属于类别ci的概率 本代码为训练阶段(Naive Bayes classification is divided into two steps: 1 Calculate the probability between the feature item and its own category; 2 The probability of judging whether the text dj belong
朴素贝叶斯
- 朴素贝叶斯算法运行和程序代码的实验与结果(Operation of naive Bayes algorithm)
朴素贝叶斯算法资料
- 朴素贝叶斯算法的相关资料，包含算法以及实验结果等。(The related data of the naive Bayes algorithm.)
adult
- 本人课设实现的基于决策树和朴素贝叶斯对Adult数据集进行分类！(Adult dataset is classified based on decision tree and naive bayes!)
NaiveBayes
- 机器学习入门经典算法中的朴素贝叶斯算法，python3.6，编译通过可运行。(Naive Bayes algorithm in machine learning classic algorithm)
python_self
- 实现了机器学习的各种分类算法，如：knn，svm，朴素贝叶斯，神经网络，决策树等。(Various classification algorithms of machine learning, KNN, SVM, naive bayes, neural network, decision tree, etc.)
bayes_analyse
- 基于代价敏感的朴素贝叶斯二分类对于不均衡数据的处理(Cost sensitive naive Bayes two classification for unbalanced data processing)