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Probabilistic model of machine learning

2022-04-23 02:40:00 【Summer melts the season】

One . Maximum likelihood estimation

More popular , Maximum likelihood estimation , Is to use the known sample results , Backward extrapolation is most likely （ Maximum probability ） The parameter value that causes this result .

Two . Maximum posterior estimate

Something happened , And the probability that it belongs to a certain category , With this posterior probability , We can classify the samples . The higher the posterior probability is , The more likely it is that something belongs to this category , The more reason we have to put it under this category .

Refer to the connection ：
https://blog.csdn.net/zengxiantao1994/article/details/72787849

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