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R language to do K-means clustering example analysis, I believe that many inexperienced people do not know what to do, so this paper summarizes the causes of the problem and solutions, through this article I hope you can solve this problem.

K-means clustering is a commonly used clustering method. The common function for k-means clustering in R language is kmeans (), which needs to input three parameters. The first is the data used in clustering, the second is how many categories k you want to cluster the data, and the third parameter is nstart https://www.datanovia.com/en/lessons/k-means-clustering-in-r-algorith-and-practical-examples/.

It is mentioned in this link

The default nstart is 1, and a higher value is recommended for a stable result. For example, you can use 25 or 50.

Well, if you want to use k-means clustering, it can be divided into two cases.

The first is to know how many categories I want to group, such as the data set of irises, and clearly want to cluster into three categories. At this time, directly specify the k-means clustering df with the iris data set under k

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