What is the best way to use JMP to do clustering analysis if the data is a mixed model

ask — Sat, 02 Dec 2023 11:18:38 GMT

What is the best way to use JMP to do clustering analysis if the data is a mixed model with continuous and categorical variables? K-Means seems to just work for continuous variables. Right? Thanks in advance.

Re: What is the best way to use JMP to do clustering analysis if the data is a mixed model

Victor_G — Mon, 04 Dec 2023 11:04:31 GMT

Hi @ask,

K-Means and Normal Mixtures are clustering methods requiring numeric columns only. You can have more details and a comparison between clustering methods here : Overview of Platforms for Clustering Observations

If you have a dataset with categorical and numeric columns, you can try the Hierarchical Cluster platform.

In this platform, you have access to various methods (Ward, Average, Centroïd, ...) , and since Hierarchical clustering do not require to specify the number of clusters apriori, this approach is interesting as it can provide an exhaustive overview of the possible links between your observations/samples at different levels.

More infos available here : Clustering | JMP

I hope this answer will help you,

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What is the best way to use JMP to do clustering analysis if the data is a mixed model

Re: What is the best way to use JMP to do clustering analysis if the data is a mixed model