Description: 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 mean class. error.
％ pbayescln - Plots discriminat function of Bayes classifier.-bayeserr- Computes the Bayesian risk for o ptimal classifier. % bayescln- Classifier bas ed on Bayesian decision rule for Gaussians. Bayes% nd- Discrim. function, dichotomy. max aposteriori probability. % bhattach- Bhat tacharya s upper limit of mean class. error. pb% ayescln- Plots discriminat function of Bayes c lassifier. Platform: |
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Author:孟庆 |
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Description: 在具有模式的完整统计知识条件下，按照贝叶斯决策理论进行设计的一种最优分类器。分类器是对每一个输入模式赋予一个类别名称的软件或硬件装置，而贝叶斯分类器是各种分类器中分类错误概率最小或者在预先给定代价的情况下平均风险最小的分类器。-In a model under the condition of complete statistical knowledge, in accordance with the Bayesian decision theory to design an optimal classifier. Classifier is the input mode of each name given to a category of software or hardware devices, and Bayesian classifier is the classifier in the smallest classification error probability or the cost of pre-given circumstances smallest average risk classifier. Platform: |
Size: 3072 |
Author:御风疾书 |
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Description: 使用matlab对基于最小错误率的Bayes分类器进行仿真，编写了相应的程序，分为协方差相等和不相等两种情况，最后画出了三类的分界线-Using matlab to the smallest error rate based on the Bayes classifier to carry out simulation, the preparation of the corresponding procedures, divided into equal covariance and unequal both cases, the final draw of the three types of line Platform: |
Size: 1024 |
Author:liz |
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Description: 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 Platform: |
Size: 2048 |
Author:liuyang |
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Description: 使用Matlab编程，对教材74页例3.3.1进行编程仿真。其中，正电压A的值、噪声方差值、每个码元周期内的采样点数N自行设定（可设置为可调的变量）。噪声值可使用Matlab中产生高斯随机数的函数来进行仿真。贝叶斯检测判决式中，先验概率P(H1)=P(H0)，判断错误的代价因子设为1，判断正确的代价因子设为0.
按照上述参数的设定进行仿真，实现对仿真数据的贝叶斯检测判决；循环生成仿真数据，并进行判决结果的统计，即记录判决正确的次数，估计正确判决的概率。(The use of Matlab programming, teaching materials 74 pages of 3.3.1 programming simulation. Among them, the value of positive voltage A, the variance of noise, the number of sampling points in each symbol cycle (N) can be set by itself (adjustable variable). Noise values can be simulated using the function of generating Gauss random numbers in Matlab. In the Bias detection decision, the prior probability P (H1) =P (H0), the factor of error judgment is set to 1, and the correct cost factor is set to 0.
According to the simulation parameters and realize the judgment of Bayesian detection simulation data; generating cycle simulation data, statistics and decision, which records the correct number of judgment, the estimated probability of correct decision.) Platform: |
Size: 1024 |
Author:妮妮111
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Description: 实验要求：
1. 以身高为例，画出男女生身高的直方图并做对比；
2. 采用最大似然估计方法，求男女生身高以及体重分布的参数；
3. 采用贝叶斯估计方法，求男女生身高以及体重分布的参数（假定方差已知，作业请注明自己选定的一些参数情况）；
4. 采用最小错误率贝叶斯决策，画出类别判定的决策面。并判断某样本的身高体重分别为(160,45)时应该属于男生还是女生？为(178,70)时呢？(Experimental requirements:
1. take height as an example, draw the height histogram of male and female students, and make a comparison;
2. the maximum likelihood estimation method was used to calculate the height and weight distribution parameters of male and female students;
3. Bayesian estimation method is used to find the parameters of height and weight distribution of male and female students (assuming variance is known, please indicate some parameters selected by homework);
4., the Bayes decision with minimum error rate is used to draw the decision surface of category decision. And determine the height and weight of a sample respectively (160,45), should belong to the boys or girls? What about (178,70)?) Platform: |
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Author:PPLL
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