搜索资源列表
BBayes_Classia
- 贝叶斯分类器，利用后验概率，对对已知属性对象进行分类可直接使用。 -Bayesian classifier using posterior probability classification known attribute object can be used directly.
Bbeiyessa
- 贝叶斯网络概率中文分词算法，，基于概率的分词算法可直接使用。 -Bayesian network probability Chinese word segmentation algorithm, probability-based segmentation algorithm can be used directly.
Bayesian-posterior-probability
- 实现贝叶斯概率计算过程。假设进行n次试生产，计算最后得到后验概率，即可信度。样本数据集个数和观测值从文件中读入，计算过程封装为动态链接库，以.dll形式提供， 主程序提供界面输入先验分布值、边缘分布值，显示计算结果。 -Bayesian probability calculation process. Assuming that the n-th trial production, and calculate the final posterior probability that cr
myBayes
- 贝叶斯分类器的分类原理是通过某对象的先验概率，利用贝叶斯公式计算出其后验概率，即该对象属于某一类的概率，选择具有最大后验概率的类作为该对象所属的类-Bayesian classifier principle a priori probability of the object using the Bayesian formula to calculate the subsequent posterior probability that the object belongs to a certa
bayes(C)
- 贝叶斯融合基本计算方法，解决后验概率的计算问题-Bayes fusion
ML.m
- 在贝叶斯分类中,用极大似然估计法估计概率分布的均值和方差-Compute the maximum-likelihood estimate of the mean and covariance matrix of each class and then uses the results to construct the Bayes decision region. This classifier works well if the classes are uni-modal, even when
bayesian0930
- j简单的贝叶斯模型数据概率求解问题，有助于理解贝叶斯模型数据分析过程。-j simple Bayesian probability model data to solve problems, help to understand the Bayesian model data analysis process.
bnt_sick
- 贝叶斯网络经典入门，建立一个简单的贝叶斯网络，并输入边缘概率，输入draw_graph（dag）可查看网络图。-a brief introduction of bayesian network
Bayes-classifier
- 贝叶斯分类器:贝叶斯分类的基础是概率推理，就是在各种条件的存在不确定，仅知其出现概率的情况下，如何完成推理和决策任务。-Bayesian classifier
NBregression
- 用朴素贝叶斯方法,knn等方法对数据进行回归,对某新闻标题可引起某种情绪的概率进行预测-Naive Bayesian approach to do data regression
tuxiangbeiyesi
- 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，将模式识别方法与图像处理技术相结合-The basic method of image classification using the minimum error probability Bias classifier, the pattern recognition method and image processing technology
tuxiangfengebeiyesi
- 将模式识别方法与图像处理技术相结合，利用最小错分概率贝叶斯分类器进行图像分类-The pattern recognition method and image processing technology are combined, using the minimum error probability Bias classifier for image classification
Bayes
- 贝叶斯相关，贝叶斯概率算法，原理计算程序。-Bayesian related Bayesian probability algorithms, principles calculation program.
biuqiu_v52
- 包括脚本文件和函数文件形式，利用贝叶斯原理估计混合logit模型的参数，包括回归分析和概率统计。- Including scr ipt files and function files in the form, Bayesian parameter estimation principle mixed logit model, Including regression analysis and probability and statistics.
miefou_v55
- 利用贝叶斯原理估计混合logit模型的参数，有循环检测，周期性检测，最大似然（ML）准则和最大后验概率（MAP）准则。- Bayesian parameter estimation principle mixed logit model, There are cycle detection, periodic testing, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion.
houmeng
- 该函数用来计算任意函数的一阶偏导数(数值方法),利用贝叶斯原理估计混合logit模型的参数，从先验概率中采样，计算权重。- This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Bayesian parameter estimation principle mixed logit model, Sampling a
bayes-classification-master
- 利用贝叶斯概率公式进行分类，在C#winform环境下进行的。-Using Bayesian probability formula for classification, in the C# winform environment.
fitting-model
- 要对单变量正态分布以及分类分布两种概率分布 模型，分别采用最大似然（ML），最大后验（MAP）以及贝叶斯估计（Bayes）的 方法进行概率密度估计。 -In this paper, the maximum likelihood (ML), maximum a posteriori (MAP) and Bayesian estimation (Bayes) methods are used to estimate the probability density of two kinds of pr
banjo.2.0.1
- 贝叶斯网络是一种概率网络，它是基于概率推理的图形化网络，而贝叶斯公式则是这个概率网络的基础。贝叶斯网络是基于概率推理的数学模型，所谓概率推理就是通过一些变量的信息来获取其他的概率信息的过程，基于概率推理的贝叶斯网络(Bayesian network)是为了解决不定性和不完整性问题而提出的，它对于解决复杂设备不确定性和关联性引起的故障有很大的优势，在多个领域中获得广泛应用。(Bias network is a probabilistic network, which is a graphical
Bayesian-Network-Structure-Learning-master
- 一般贝叶斯网络的构建是首先由相关领域的专家根据事物间的关系来确定出结构模型，即有向无环图，然后再利用其它方法确定每个节点的条件概率，但这样构建的网络模型无法保证其客观性和可靠性．(In general, the construction of Bayesian network is to determine the structural model, i.e. directed acyclic graph, by experts in related fields according to th