k-means clustering
The k-means algorithm was devised by MacQueen in 1967 and is one of the simplest unsupervised learning algorithms used for solving the clustering problem. It classifies a given data set through a predefined of clusters (set by the parameter k). Data points inside a cluster are homogeneous and heterogeneous to peer groups.
Applications
- The k-means algorithm was used in a gene expression study to zoom in on a small subset of novel light-regulated RNA molecules in Arabidopsis thaliana from microarray data ref
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