A model-based clustering of expectation–maximization and <i>K</i>-means algorithms in crime hotspot analysis-Reference-Cited by-同舟云学术

A model-based clustering of expectation–maximization and K-means algorithms in crime hotspot analysis

Published:2022-05-15 Issue:1 Volume:9 Page:
ISSN:2768-4830
Container-title:Research in Mathematics
language:en
Short-container-title:Research in Mathematics

Author:

Appiah Simon Kojo¹²^ORCID,Wirekoh Kingsley¹³^ORCID,Aidoo Eric Nimako¹³^ORCID,Oduro Samuel Dua⁴^ORCID,Arthur Yarhands Dissou⁵^ORCID

Affiliation:

1. Department of Statistics and Actuarial Science, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

2. KNUST-Laboratory for Interdisciplinary Statistical Analysis (LISA), Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

3. Bloomberg Philanthropies Initiative for Global Road Safety (BIGRS), Kumasi Metropolitan Assembly, Kumasi, Ghana

4. Data Science & Analytics Team, easyJet Airline Company, London Luton Airport, Luton, Berdforshire, UK

5. Department of Mathematics Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/27684830.2022.2073662

Reference56 articles.

1. Crime Analysis using K-Means Clustering

2. Classics in Environmental Criminology

3. Bahar, E. (2011). Mixture model cluster analysis under different covariance structures using information complexity [Master’s Thesis]. University of Tennessee. https://trace.tennessee.edu/utk_gradthes/968

4. A Survey of Clustering Data Mining Techniques

5. Robberies in Chicago: A Block-Level Analysis of the Influence of Crime Generators, Crime Attractors, and Offender Anchor Points

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