loading
Papers

Research.Publish.Connect.

Paper

Authors: Shengkun Xie 1 ; Anna T. Lawniczak 2 and Zizhen Wang 2

Affiliations: 1 University of Toronto Mississauga and Ryerson University, Canada ; 2 University of Guelph, Canada

ISBN: 978-989-758-222-6

Keyword(s): Spatially Constrained Clustering, Ratemaking, Geocoding, Gap Statistic, Business Data Analytic, Model Selection.

Related Ontology Subjects/Areas/Topics: Applications ; Clustering ; Economics, Business and Forecasting Applications ; Model Selection ; Pattern Recognition ; Theory and Methods

Abstract: In this work, spatially constrained clustering of insurance loss cost is studied. The study has demonstrated that spatially constrained clustering is a promising technique for defining geographical rating territories using auto insurance loss data as it is able to satisfy the contiguity constraint while implementing clustering. In the presented work, to ensure statistically sound clustering, advanced statistical approaches, including average silhouette statistic and Gap statistic, were used to determine the number of clusters. The proposed method can also be applied to demographical data analysis and real estate data clustering due to the nature of spatial constraint.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.81.29.254

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Xie, S.; Lawniczak, A. and Wang, Z. (2017). Spatially Constrained Clustering to Define Geographical Rating Territories.In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 82-88. DOI: 10.5220/0006118100820088

@conference{icpram17,
author={Shengkun Xie. and Anna T. Lawniczak. and Zizhen Wang.},
title={Spatially Constrained Clustering to Define Geographical Rating Territories},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={82-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006118100820088},
isbn={978-989-758-222-6},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Spatially Constrained Clustering to Define Geographical Rating Territories
SN - 978-989-758-222-6
AU - Xie, S.
AU - Lawniczak, A.
AU - Wang, Z.
PY - 2017
SP - 82
EP - 88
DO - 10.5220/0006118100820088

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.