Cargando…
DDCAL: Evenly Distributing Data into Low Variance Clusters Based on Iterative Feature Scaling
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 without over-emphasizing outliers. This enabl...
| Autores principales: | , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873542/ https://www.ncbi.nlm.nih.gov/pubmed/36713890 http://dx.doi.org/10.1007/s00357-022-09428-6 |