publication . Article . Conference object . 2016

Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions-a crime case study

Monsuru Adepeju; Gabriel Rosser; Tao Cheng;
Open Access English
  • Published: 07 Apr 2016
  • Publisher: Taylor & Francis
  • Country: United Kingdom
Abstract
Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squared error. Statistical likelihood is a valid alternative, but this does not measure absolute performance and is therefore difficult for practitioners and researchers to int...
Subjects
free text keywords: Geography, Planning and Development, Library and Information Sciences, Information Systems, Point process, hotspot, prediction, space-time, crime, Space time, Point process, Prediction methods, Complementarity (molecular biology), Crime data, Artificial intelligence, business.industry, business, Mean squared error, Hotspot (Wi-Fi), Machine learning, computer.software_genre, computer, Computer science, Data mining, Regression analysis
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