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bayes
- 将模式识别方法与图像处理技术相结合，掌握利用最小错分概率贝叶斯分类器进行图像分类的基本方法-bayes with matlab
Bayes
- 本程序是使用的Python写的一个Bayes分类器，通过这个程序可以大致掌握Bayes的原理。-This procedure is used to write a Python Bayes classifier, through this program can be broadly master the principles of Bayes.
bayes
- 基于自然对数改进的朴素贝叶斯,统计TPR,NPR,TFR,TPR-Based on the natural logarithm improved Naive Bayes
Bayes-thresholding
- Bayes shrink for image denoising
bayes
- Bayes理论相关论文和代码, Bayes理论相关论文和代码,-bayes paper and code
Naive-bayes
- 本文以拼写检查作为例子，讲解Naive Bayes分类器是如何实现的。对于用户输入的一个单词（words），拼写检查试图推断出最有可能的那个正确单词（correct）。当然，输入的单词有可能本身就是正确的。比如，输入的单词thew，用户有可能是想输入the，也有可能是想输入thaw。为了解决这个问题，Naive Bayes分类器采用了后验概率P(c|w)来解决这个问题。P(c|w)表示在发生了w的情况下推断出c的概率。为了找出最有可能c，应找出有最大值的P(c|w)，即求解问题-In this
Bayes
- 贝叶斯机的java实现。机器学习代码，在学习中实现的一些代码。概率论与数理统计-bayes source code
Naive-Bayes
- Python实现朴素贝叶斯分类，即Naive Bayes Classifier（NB），数据集为pima-indians印第安人糖尿病数据集。-Python implementation naive Bayes classifier, i.e. Naive Bayes Classifier (NB), the data set is pima-indians Indians diabetes data sets.
Naive-Bayes
- 朴素贝叶斯的matlab代码，概率分类模型。-MATLAB code for Naive Bayes model, a probability classification algorithm.
Bayes方法基础
- 贝叶斯是无敌的，贝叶斯是万能的，贝叶斯是全知全能的(bayes is powerful ,bayes is wonderful)
bayes
- 基于概率论的分类方法 :朴素贝叶斯 学习朴素贝叶斯算法进行简单的二值分类(Classification method based on probability theory: Naive Bayes Learning naive Bayes algorithm for simple two valued classification)
朴素贝叶斯源码
- 朴素贝叶斯分类器用Python实现，基础代码适合初学者(Naive bayes classifier is implemented in Python, and basic code is suitable for beginners)
Naive Bayes Classifier - Copy-2
- This is a simple probabilistic classifier based on the Bayes theorem, from the Wikipedia article. This project contains source files that can be included in any C# project.
bayes
- Bayes分类器，对随机产生的1000组数据进行分类，模式识别课作业(Bayes classifiation.m)
Bayes classifier
- 基于贝叶斯分类器的数据处理与MATLAB实现(Data processing based on MATLAB implementationof Bayes classifier)
face-Bayes-GaussianNB
- 用贝叶斯中的高斯类库实现人脸识别，结合PCA算法实现(Face recognition using the Gauss class library in Bayes, combined with PCA algorithm)
bayes
- 自己书写的一段机器学习的朴素贝叶斯算法，基于Python实现(The Implementation of Bayes Algorithm in Python)
BAYES
- 针对高斯白噪声中二元确知信号，仿真信号检测过程，分析检测门限、噪声的方差及取样间隔对检测的影响检测。(For binary Gaussian white noise signal, simulation signal detection process, analysis of detection threshold, noise variance and sampling interval on the detection of the impact of detection.)
Naive Bayes
- 调用于sklearn平台的朴素贝叶斯算法，有着较好的分类能力(The naive bayes algorithm for sklearn platform is a good classification capability.)
Gauss Bayes
- 使用高斯贝叶斯函数对已有数据进行分类，有样本集(The Gauss Bayes function is used to classify the existing data.)