2018/03/21 by Geoff Boeing, Boeing, Geoff
Computer Science · #Advanced Clustering Algorithms Research #Data Management and Algorithms #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
paper · pdf · doi:10.48550/arxiv.1803.08101
openalex publication_date 2018/03/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Traditionally it had been a problem that researchers did not have access to enough spatial data to answer pressing research questions or build compelling visualizations. Today, however, the problem is often that we have too much data. Spatially redundant or approximately redundant points may refer to a single feature (plus noise) rather than many distinct spatial features. We use a machine learning approach with density-based clustering to compress such spatial data into a set of representative features.