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对于第三问
当sigma
给定并趋于0时,EM中的初始化相当于对k个类的均值进行初始化,这与k-means中给定一个初始化的分割计算均值是类似的。
在EM的E步计算responsibilities时,也就是考虑每个类对观测点的影响,然后在M步通过加权求均值产生新的均值;这与k-menas中每个点选择其最近的均值点然后重新计算类的均值点是类似的。
最后两个算法都采用迭代来得到最终的均值(均值点)估计。
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Related Issues (20)
- Phoneme Data
- Ex. 6.8 HOT 1
- Ex. derive natural spline bases from B-spline bases HOT 2
- Ex. 9.5 HOT 7
- unclickable nav in the header
- Ex. 9.6 HOT 6
- broken gravatar for mainland China HOT 1
- disappeared avatar on the n-th (n>=2) level in phones from mainland China
- workflow for Rmd notes
- ok
- Fig. 18.1 HOT 5
- Ex 8.1 HOT 1
- Ex. 2.2
- Chapter 1.1 - Website URL of ESL is unavailable HOT 1
- Fig. 8.6 and Tab. 8.2: Example for EM HOT 2
- 请问一下,链接是不是失效了呀?那个网址esl.hohoweiya.xyz进不去了 HOT 2
- Ex. 3.7 HOT 1
- Fig. 14.29 HOT 1
- Fig. 14.30 HOT 1
- Can you tell me how the recursive computational spline basis functions of Computations for Splines (B-splines) can be used on natural cubic spline? HOT 4
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