文件名称:PR代码及资料
- 所属分类：
- 人工智能/神经网络/遗传算法
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- 上传时间：
- 2019-05-10
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- 6.3mb
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- 0次
- 提 供 者：
- 良*
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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（注明自己选定的参数情况）；
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. Take the height as an example, draw the histogram of the height of boys and girls and make a comparison. 2. Using the maximum likelihood estimation method, the parameters of height and weight distribution of male and female students are obtained. 3. Using Bayesian estimation method, the parameters of height and weight distribution of male and female students were calculated (indicating the parameters selected by themselves). 4. Using Bayesian decision-making with minimum error rate, the decision-making surface of category decision-making is drawn. When the height and weight of a sample are (160,45), should it belong to boys or girls? For (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（注明自己选定的参数情况）；
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. Take the height as an example, draw the histogram of the height of boys and girls and make a comparison. 2. Using the maximum likelihood estimation method, the parameters of height and weight distribution of male and female students are obtained. 3. Using Bayesian estimation method, the parameters of height and weight distribution of male and female students were calculated (indicating the parameters selected by themselves). 4. Using Bayesian decision-making with minimum error rate, the decision-making surface of category decision-making is drawn. When the height and weight of a sample are (160,45), should it belong to boys or girls? For (178,70)?)
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