R Programming

K means Clustering

R has an amazing variety of functions for cluster analysis. K-means Clustering is the most popular partitioning method. There is no outcome to be predicted, and the algorithm just tries to find patterns in the data. K-Means clustering ignores model types (nominal and ordinal), and treat all numeric columns as continuous columns. In k means clustering, one has to specify the number of clusters which he want the data to be grouped into. K-Means clustering only supports numeric columns. With smaller data tables, the results can be highly sensitive to the order of the observations in the data table.

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