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贝叶斯优化算法是一种新的演化算法，通过贝叶斯概率统计的知识来学习后代，可是使演化朝有利的方向前进，程序用C实现了贝叶斯优化算法。-Bayesian Optimization Algorithm is a new evolutionary algorithm, through Bayesian probability and statistics to learn the knowledge of future generations, but to enable the evolution to
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bayeserr - Computes the Bayesian risk for optimal classifier.
％ bayescln - Classifier based on Bayes decision rule for Gaussians.
％ bayesnd - Discrim. function, dichotomy, max aposteriori probability.
％ bhattach - Bhattacharya s upper limit of
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The BNL toolbox is a set of Matlab functions for defining and estimating the
parameters of a Bayesian network for discrete variables in which the conditional
probability tables are specified by logistic regression models. Logistic regression can be
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最小错误概率贝叶斯分类器的matlab程序，可用于二维数据的分类以及分类效果的图像显示，可帮助初学者加深对贝叶斯分类算法的理解。-This is a matlab program of the minimum probability of error of Bayesian classifier.Which can display the image of two-dimensional data classification and the classification results . I
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用k2算法从先验概率构建贝叶斯网络，实现推理，结构学习，参数学习用贝叶斯方法。-K2 algorithm using Bayesian network built from the a priori probability to achieve reasoning, structure learning, parameter learning.
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讲授贝叶斯原理，是概率论中很重要的一个分支-Bayesian principles of teaching is very important in probability theory a branch of
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模拟网络通信，对其中的信息进行统计，用贝叶斯算法计算特定信息的后验概率，自动日志-Simulation of network communications, for which statistical information, using Bayesian algorithm-specific information on a posteriori probability, automatic log
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基于贝叶斯理论的指纹识别算法及学习套件, 使用贝叶斯概率论实现对指纹识别,特征码提取,特征对数获取的功能-Based on Bayesian theory and learning algorithm for fingerprint identification kits, the use of Bayesian probability theory to achieve fingerprint, signature extraction, characteristics of the func
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贝叶斯决策包含最小风险和最小错误概率两种情况的仿真-Bayesian decision-making included the minimum risk and minimum error probability of the two simulation
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贝叶斯分类器，利用后验概率，对已知属性对象进行分类-Bayesian classifier, the use of posterior probability of the known properties of the object classification
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这系列课件系统地讲述了模式识别的基本理论和基本方法。内容涵盖了贝叶斯决策、概率密度函数的估计、线性判别函数、邻近法则、特征的选择和提取、非监督学习、神经网络、模糊模式识别等。-This series of courseware on a pattern recognition system to the basic theory and basic methods. Covers the Bayesian decision-making, the estimated probability de
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建立贝叶斯网络，草地湿的条件概率网络。计算边缘概率，联合分布。-The establishment of Bayesian networks, conditional probability network of wet grass. Computing marginal probabilities, the joint distribution.
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突变分为如下主要的几种：均值突变（最常见）、方差突变、线性回归突变（也称趋势突变）、概率突变、空间型突变、谱突变、模型参数突变，等等。贝叶斯突变检测属于概率突变检测方法，其特点是能给出突变点的概率分布图。-Mutations are divided into the following main categories: the mean mutation (the most common), variance mutation, linear regression mutation (also
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贝叶斯学习概率的算法设计Bayesian probability algorithm-Bayesian probability Bayesian probability algorithm algorithm
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用监督参数估计中的贝叶斯方法估计条件概率密度的参数u-With the supervision of the Bayesian estimation method to estimate the parameters of the conditional probability density of u
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实现贝叶斯最大后验概率计算，适合原理的研究，简单易懂。-To achieve the maximum a posteriori Bayesian probability, the principle of appropriate and easily understood.
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Builds BN from topological
structure information and probability model
and predict diagnose from evidences using
BN inference
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用套抽样算法实现一些贝叶斯概率模型的计算-Implement some of Bayesian probability calculation model with a set of sampling algorithm
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matlab语言实现LDA模型，即：三层贝叶斯概率模型，包含词、主题和文档三层结构。运行简单，容易理解。-MATLAB language implementation of the LDA model, namely: three layer Bayesian probability model, including words, themes and documents of the three layer structure. Easy to operate, easy to underst
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贝叶斯分类算法是统计学的一种分类方法，它是一类利用概率统计知识进行分类的算法(Bayes classification algorithm is a classification method of statistics, which is a classification algorithm using probability statistics)
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