搜索资源列表
CPP-naive-bayes
- 用c++编写的经典贝叶斯算法，非常适合初学者，建议看看！-Using c++ to write the classic Bayesian algorithm is very suitable for beginners, it is recommended to take a look!
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
DEAP04JFisherNaiveBayes
- J fisher discriminant for high/low classes. Naive Bayes classifier for EEG feature selection. - Both for evaluating high/low levels of Valence or Arousal.
nBayes-master
- implmentation on naive bayes algotethem in c#
bayes
- 基于朴素贝叶斯预测的一个小例子（根据ppt里的例子），将就着看，内有bayes的讲解ppt -开发环境vs2012，c-Based on a small example of Naive Bayesian prediction (based on ppt in the example), will the see, there are explanations bayes ppt - development environment vs2012
NBC
- 迁移朴素贝叶斯分类器算法实现，可用于高光谱遥感图像处理-Migration naive Bayes classifier algorithm can be used for hyperspectral remote sensing image processing
eMailSystem
- 采用有监督的朴素贝叶斯、SVM和KNN算法对进行训练，实现对邮件的分类-Using supervised naive bayes, SVM and KNN algorithm for training, implementation of the classification of the mail
NaiveBayesClassifier
- implementation naive bayes clasifier
MachLearn_ml
- MachLearn:已经实现了朴素贝叶斯分类器、决策树、支持向量机算法。在Linux上可成功编译-MachLearn: has achieved a naive Bayes classifier, decision trees, support vector machine algorithm. Successfully compile on Linux
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
code
- 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.-in machine learning, naive Bayes classifiers are a family
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.
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)
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
Bayes
- 最简单的朴素贝叶斯程序，其中的数据上花种的分类情况。(Naive Bayesian program is the most simple, the classification of the data on the flowers.)
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#)
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)