版权声明:本文为博主原创文章,未经博主同意不得转载。 https://blog.csdn.net/wxcdzhangping/article/details/31366143

问题:

       设数据集核K-均值聚类(Kernel K-means Clustering)。当中核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering)。Mercer核函数核K-均值聚类(Kernel K-means Clustering)。依据Mercer定理存在映射核K-均值聚类(Kernel K-means Clustering),使得核K-均值聚类(Kernel K-means Clustering)

        核K-均值聚类就是讨论映射数据集核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering)空间中的聚类情况,设在核K-均值聚类(Kernel K-means Clustering)空间中。把数据集分为核K-均值聚类(Kernel K-means Clustering)类,核K-均值聚类(Kernel K-means Clustering)为第核K-均值聚类(Kernel K-means Clustering)类的均值,核K-均值聚类(Kernel K-means Clustering)

即考虑下面模型:

核K-均值聚类(Kernel K-means Clustering)

核K-均值聚类(Kernel K-means Clustering)


问题1:

怎么训练上述模型。由于核K-均值聚类(Kernel K-means Clustering)普通情况下是解不出来的。

方法:

初始化核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering),当中核K-均值聚类(Kernel K-means Clustering)

核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering)

E步:求核K-均值聚类(Kernel K-means Clustering)

核K-均值聚类(Kernel K-means Clustering)

注意当中:

核K-均值聚类(Kernel K-means Clustering)核K-均值聚类(Kernel K-means Clustering)

M步:固定核K-均值聚类(Kernel K-means Clustering),求核K-均值聚类(Kernel K-means Clustering)

核K-均值聚类(Kernel K-means Clustering)

核K-均值聚类(Kernel K-means Clustering),

核K-均值聚类(Kernel K-means Clustering)

当中核K-均值聚类(Kernel K-means Clustering)

进入下一轮迭代。直至收敛!




相关文章:

  • 2021-09-29
  • 2022-01-15
  • 2021-11-03
  • 2022-12-23
  • 2021-07-22
  • 2022-12-23
  • 2021-05-08
  • 2021-11-29
猜你喜欢
  • 2021-08-20
  • 2022-12-23
  • 2021-04-29
  • 2021-08-23
  • 2021-04-26
  • 2021-11-17
相关资源
相似解决方案