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bayes4
- 用matlab软件编程，实现bayes分类问题4。-Matlab program, bayes classification.
Bayes
- 一个matlab写的动态链接库，实现贝叶斯运算，源码里面也有，C#可以直接调用其中的DLL文件，测试有效。-Write a matlab dynamic link library that implements the Bayesian computing source inside the C# can directly call the DLL files, test Effect.
stprtool22oct09
- 是一个模式识别工具包，里面包含bayes,linear分类函数，还有支持向量机SVM工具包-It is a pattern recognition toolbox, which contains the bayes, linear classification function, as well as support vector machines SVM toolbox
BayesianClassificationAlgorithmsCPP
- 本代码能够实现了两类模式的贝叶斯分类器分类-This code will be able to realize the two kinds of patterns bayes classifier classification
beiyesifenlei
- 朴素贝叶斯分类系统，模式识别的参考程序，供学习者参考。-navies bayes
CPP
- 朴素贝叶斯文本 分类接口实现源码，C/C++接口实现文本分类-Naive Bayes text text classification interface implementation source code in C/C++ interface text classification
MATERIAL-DMSPSO
- source codes for bayes classifier
matlab_signal_test
- 1.用最大似然比的方法检测信号、判别概率等。2.Bayes检测方法检测信号。3.判别风险系数-test signal discrimination probabilityusing A maximum likelihood ratio . 2.Bayes detection methods . 3 discriminant risk factor
T-HOMEWORK
- 用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。-Use Parzen Wi
pattern-recognition
- 模式识别的内容，包括模式识别的基本概念、模式识别方法及应用。具体的内容包括：正则化网络、Bayes决策理论、分类器组合、统计学习理论、概率密度估计、非监督学习方法-Pattern recognition, including the basic concepts of pattern recognition, pattern recognition methods and applications.Specific content, including: Regularization Netwo
PatternRecognition
- 模式识别手写数字图像识别（最小错误率Bayes算法）-digital image Least error Bayes
gender-classification
- Parzen窗法估计概率密度函数，得出贝叶斯分类器 用Fisher线性判别方法求分类器 留一法估计错误率-Parzen Fisher Bayes Leave-one based on height and weight
TutorMatlab
- MATLAB PROGARM Naive Bayes
CS-recovery-based-on-bayes
- 基于贝叶斯假设的压缩感知重构算法，介绍了算法迭代流程，并与OMP ROMP STOMP算法做了比较-Bayesian Hypothesis Testing Based Recovery for Compressed Sensing
u
- 基于正态分布的最小错误率Bayes分类器-Minimum error rate Bayes classifier based on normal distribution
risk
- 基于正态分布下的最小风险Bayes分类器-Minimum risk Bayes classifier based on normal distribution
lfd_2005_naive
- Why Naive Bayes? Naive Bayes is one of the simplest density estimation methods from which we can form one of the standard classiˉcation methods in machine learning.
Bayesian-based-classifier-design
- 基于贝叶斯的分类器设计.用“cancer.mat”的数据作为训练样本集，建立Bayes分类器，用测试样本数据对该分类器进行测试，从而加深对所学内容的理解和感性认识。-Based on the Bayes classifier. ' Cancer.mat data as the training sample set, the establishment of the Bayes classifier, the classifier is tested with the test sampl
NBC
- 实现朴素贝叶斯的分类，很好用的，利用matlab编写，不错的程序-Naive Bayes classification, well used, the use of Matlab prepared, a good program
but_ssdut
- bayes分类器，通过前期依靠样本自身的训练学习实现对信息，数据，图像等的分类判断，分析，处理-bayes classifier, rely on samples through pre-training to learn the judgment on the classification of information, data, images, analysis, processing