Spatial process-based transfer learning for prediction problems
| Year of publication: |
2025
|
|---|---|
| Authors: | Murakami, Daisuke ; Kajita, Mami ; Kajita, Seiji |
| Published in: |
Journal of geographical systems : geographical information, analysis, theory, and decision. - Berlin : Springer, ISSN 1435-5949, ZDB-ID 1481603-9. - Vol. 27.2025, 1, p. 147-166
|
| Subject: | Crime | Gradient boosting | Spatial prediction | Spatial process | Transfer learning | Prognoseverfahren | Forecasting model | Kriminalität | Theorie | Theory | Räumliche Verteilung | Spatial distribution | Lernprozess | Learning process | Regionalökonomik | Regional economics | Räumliche Interaktion | Spatial interaction | Lernen | Learning |
-
K-nearest neighbors prediction and classification for spatial data
Ahmed, Mohamed-Salem, (2023)
-
Lin, Xu, (2022)
-
A spatial one-sided error model to identify where unarrested criminals live
Puerta-Cuartas, Alejandro, (2025)
- More ...
-
Crime prediction by data-driven Green's function method
Kajita, Mami, (2020)
-
Tourism development and propaganda in contemporary Lhasa, Tibet Autonomous Region (TAR), China
Murakami, Daisuke, (2008)
-
Mori, Tomoya, (2025)
- More ...