Significant DBSCAN+: Statistically Robust Density-based Clustering
Yiqun Xie; Xiaowei Jia; Shashi Shekhar; Han Bao; Xun Zhou · 2021 · ACM Transactions on Intelligent Systems and Technology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with…
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WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: Crossref · DOI 10.1145/3474842