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文件名称:work
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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？(1) taking height as an example, draw the histogram of male and female students and compare them;
2) the maximum likelihood estimation method was used to calculate the height and weight distribution parameters of male and female students;
3) using Bayesian estimation method to find the parameters of height and weight distribution of male and female students (assuming the variance is known, please indicate some of the parameters selected by the job);
4) using the minimum error rate Bayes decision, 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)?)
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？(1) taking height as an example, draw the histogram of male and female students and compare them;
2) the maximum likelihood estimation method was used to calculate the height and weight distribution parameters of male and female students;
3) using Bayesian estimation method to find the parameters of height and weight distribution of male and female students (assuming the variance is known, please indicate some of the parameters selected by the job);
4) using the minimum error rate Bayes decision, 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)?)
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