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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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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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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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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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考虑两个参数的一维三角概率模型,用贝叶斯方法对其进行估计,了解贝叶斯估计方法.-Consider the two parameters of one-dimensional triangular probability model, using Bayesian methods to estimate their understand Bayesian methods.
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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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一种空时贝叶斯压缩感知算法,用在认知无线电中,大大提高了检测概率-Perception of space-time compression of a Bayesian algorithm, used in the cognitive radio, greatly improving the detection probability
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基于matlab的贝叶斯网络预测模型,能够预测事件发生的概率。-Matlab based on Bayesian network model to predict the probability of events.
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贝叶斯分类器的分类原理是通过某对象的先验概率,本文详细介绍贝叶斯分类器,使用贝叶斯分类器对样本进行训练分类,得到良好分类结果,并对分类结果进行分析。-Principle of Bayesian classifiers is through prior probability of an object, the paper describes Bayesian classifier, Bayesian classifier using the training sample classificat
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Occupancy Grid Mapping: using bayesian rules to update the grid probability of occupancy for only static coordinate (the probability describe the cell is occupied or not or unknown)
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这是模式识别中最小错误率Bayes分类器设计方案。
自行完善了在不同先验概率的条件下,男、女错误率和总错误率的统计,放入各个数组当中。
全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。
调用最大似然估计求取概率密度子函数时,第一步获取样本数据,存储为矩阵;第二步对矩阵的每一行求和,并除以样本总数N,得到平均值向量;第三步是应用公式(3-43)采用矩阵运算和循环控制语句,求得协方差矩阵;第四步通过协方差矩阵求得方差和相关系数,从而得到概率密度
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这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下,自行完善了在一定先验概率的条件下,男、女错误率和总错误率的统计,放入各个数组当中。
全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。
调用最大似然估计求取概率密度子函数时,第一步获取样本数据,存储为矩阵;第二步对矩阵的每一行求和,并除以样本总数N,得到平均值向量;第三步是应用公式(3-43)采用矩阵运算和循环控制语句,求得协方差矩阵;第四步通过协方差矩阵求得方差和相关系数,从
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这是用身高体重数据进行性别分类的实验。
用最小错误率贝叶斯分类器决策时,首先通过比较概率大小判断一个体重身高二维向量代表的人是男是女,然后再逐一与已知性别的数据比较,就可以得到错误率的统计。然后改变先验概率,重复上面的过程,观察数据结果的变化。
用最小风险贝叶斯分类器决策时,首先求出用最小错误率贝叶斯分类器得到的条件概率;然后根据人为给定的决策表,根据公式算出条件风险;然后逐一比较条件风险,找出使条件风险最小的决策(也就是分类)。最后用分类得到的结果逐一比较已经知道的原始数据,统计处错误
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这是最小错误概率贝叶斯程序 测试效果较好 大家-This is the minimum error probability of Bayesian procedures to test the effect of good everybody have a look
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基于最小错误概率和最小风险的贝叶斯分类器-Based on the minimum probability of error and minimum- risk Bayesian classifier
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基于最小错误概率的贝叶斯分类,用于数字识别分类-Based on minimum error probability Bayesian classifier for Digital Identification and Classification
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贝叶斯最小错误率分类器 用两列数据属性求二维正态分布 求后验概率分类-Bayesian minimum error rate sorter two columns of data attributes seeking seeking a two-dimensional normal posterior probability classification
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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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