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DDCAL: Evenly Distributing Data into Low Variance Clusters Based on Iterative Feature Scaling

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This work studies the problem of clustering one-dimensional data points such that they are evenly distributed over a given number of low variance clusters. One application is the visualization of data on choropleth maps or on business process models, but witho... ...