确定时间序列数据的SOM(自组织图)中的集群成员资格 [英] Determining cluster membership in SOM (Self Organizing Map) for time series data

问题描述

我还在从事一个需要对时间序列数据进行聚类的项目.我正在使用在MATLAB中可用于集群目的的SOM工具箱，并遇到以下问题: 我们如何确定哪些数据属于哪个集群?" SOM从数据集中随机选择数据样本，并为每个数据样本找到BMU.据我所知，在SOM算法中，数据样本标识符不被视为数据的维数.如果是这种情况，那么我们如何跟踪样本?我认为som_bmus不能解决此问题.您知道如何在不更改SOM工具箱中包含的任何功能的情况下进行操作吗?

I am also working on a project that requires clustering of time series data. I am using the SOM toolbox that works in MATLAB for clustering purpose and stuck with the following problem: "How can we determine which data belongs to which cluster?" SOM randomly chooses data sample from dataset and finds BMU for each data sample. As far as I know, data sample identifier is not regarded as dimension of data in SOM algorithm. If it is the case then how can we track the samples? I don't think that som_bmus solves this issue. Any idea how you do it without changing any functions included in SOM toolbox?

推荐答案

y=vec2ind(output)

将为您提供MATLAB生成的输出的索引号.借助此信息，您可以查看哪些输入数据属于哪个神经元#.

will give you the index number for the output generated by MATLAB.With this information,you can see which input data belongs to which neuron#.

只需直接在脚本中使用上面的代码，其余的就会完成.

Just use the above code directly in your script, it will do the rest.

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