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University of Toronto Press
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Common methods for classifying choropleth map features typically form classes based on a single feature attribute. This technical note reviews the use of the k-means clustering algorithm to perform feature classification using multiple feature attributes. The k-means clustering algorithm is described and compared to other common classification methods, and two examples of choropleth maps prepared using k-means clustering are provided.
Polczynski, Mark and Polczynski, Michael, "Using the k-Means Clustering Algorithm to Classify Features for Choropleth Maps" (2014). Electrical and Computer Engineering Faculty Research and Publications. 98.
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