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This article introduces the relevant knowledge of "what is the application of clustering function in R language". In the operation of actual cases, many people will encounter such a dilemma. Next, let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Systematic clustering Hierarchical clustering (hierarchical clustering, pedigree clustering)-shortest distance method (single linkage)-longest distance method (complete linkage)-intermediate distance method (median method)-variable distance method (flexible median)-center of gravity

Systematic clustering Hierarchical clustering (hierarchical clustering, pedigree clustering)

-shortest distance method (single linkage)

-longest distance method (complete linkage)

-median distance method (median method)

-variable distance method (flexible median)

-Gravity method (centroid)

Class averaging method (average)

-variable class averaging (flexible average)

-Ward least variance method (Ward's minimum variance)

In Shengxin industry, the above clustering methods are often used to cluster biological data, such as the application of common correlation clustering function in R: hclust () parameter method:

"single" shortest distance method

"complete" longest distance method

"median" intermediate distance method (= WPGMC)

"average" class average method (= UPGMA)

"centroid" centroid method (= UPGMC)

Sum of squares of "ward" deviation

"Mcquitty" similarity analysis (= WPGMA)

It should be noted that there may be differences in the actual hierarchical clustering methods for different languages or functions, which need to be explored.

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