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This article introduces what genealogy clustering in R language clustering algorithm refers to, the content is very detailed, interested friends can refer to, hope to be helpful to you.

1. Principle analysis:

There is no need to set the number of categories K first, because it only clusters the two nearest samples / clusters into one class in each iteration, and its operation process will naturally get the clustering results of Knowl to Karmn categories.

two。 Application in R language

Pedigree clustering (Hierarchical Method) is mainly applied to the three functions of hclust (), cutree () and rect.hclust () in stats package (R language built-in package).

Hclust (dmem method = "complete", members=NULL)

Cutree (tree,k=NULL,h=NULL)

Rect.hclust (tree,k=NULL,which=NULL,x=NULL,h=NULL,border=2,cluster=NULL)

3. Taking iris dataset as an example for analysis

1) apply the model and view the corresponding parameters of the model

2) make graphics

Plot (fit_hc)

On the R language clustering algorithm in the pedigree clustering refers to what is shared here, I hope the above content can be of some help to everyone, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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