Is-ClusterMPP: clustering algorithm through point processes and influence space towards high-dimensional data

DOI10.1007/s11634-019-00379-2zbMath1474.62230OpenAlexW2990751717WikidataQ126652512 ScholiaQ126652512MaRDI QIDQ2228285

Khadidja Henni, Ahmed Moussa, Brigitte Vannier, Pierre-Yves Louis

Publication date: 17 February 2021

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-019-00379-2

zbMATH Keywords

marked point processesdensity-based clusteringspatial data analysisGibbs cost/objective functionhigh-dimensional real data setsinfluence spaceMCMC/Monte Carlo technique

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

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