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Articles

Predicting (de-)escalation of sub-national violence using gradient boosting: Does it work?

Pages 841-859 | Received 16 Dec 2020, Accepted 07 Dec 2021, Published online: 08 Mar 2022

References

  • Apley, Daniel W., and Jingyu Zhu. 2020. “Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models.” Statistical Methodology, Series B 82 (4): 1059-1086. doi:10.1111/rssb.12377.
  • Bartusevičius, Henrikas, and Kristian Skrede Gleditsch. 2019. “A Two-Stage Approach to Civil Conflict: Contested Incompatibilities and Armed Violence.” International Organization 73 (1): 225–248. doi:10.1017/S0020818318000425.
  • Bell, Curtis, Besaw, Clayton., Frank, Matthew. 2021. “The Rulers, Elections, and Irregular Governance (REIGN) Dataset.” Broomfield, CO: One Earth Future. Accessed June 26, 2020. https://oefdatascience.github.io/REIGN.github.io/.
  • Boschee, Elizabeth, Jennifer Lautenschlager, Sean O'Brien, Steve Shellman, and James Starz. 2018. “ICEWS Weekly Event Data.” Harvard Dataverse. Accessed November 15, 2021. doi:10.7910/DVN/QI2T9A.
  • Breiman, Leo. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
  • Chen, Tianqi, and Carlos Guestrin. 2016. “XGBoost: A Scalable Tree Boosting System.” In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, edited by Balaji Krishnapuram, Mohak Shah, Alex Smola, Charu Aggarwal, Dou Shen, and Rajeev Rastogi, 785–94. New York: Association for Computing Machinery. Accessed November 10, 2021. doi:10.1145/2939672.2939785.
  • CIESIN. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11.” Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). Accessed November 10, 2021. doi:10.7927/H49C6VHW.
  • Coppedge, Michael, John Gerring, Carl Henrik Knutsen, Staffan I. Lindberg, and Jan Teorell, 2020. “V-Dem Country-Year Dataset V10.” University of Gothenburg: Varieties of Democracy (V-Dem) project.
  • Cunen, Céline, Nils Lid Hjort, and Håvard Mokleiv Nygård. 2020. “Statistical Sightings of Better Angels: Analysing the Distribution of Battle-Deaths in Interstate Conflict over Time.” Journal of Peace Research 57 (2): 221–234. doi:10.1177/0022343319896843.
  • Czado, Claudia, Tilmann Gneiting, and Leonhard Held. 2009. “Predictive Model Assessment for Count Data.” Biometrics 65 (4): 1254–1261. doi:10.1111/j.1541-0420.2009.01191.x.
  • Global Burden of Disease Collaborative Network. 2018. Global Burden of Disease Study 2017 (GBD 2017) All-cause Mortality and Life Expectancy 1950–2017. Seattle: Institute for Health Metrics and Evaluation (IHME). Accessed January 14, 2020. http://ghdx.healthdata.org/record/ihme-data/gbd-2017-all-cause-mortality-and-life-expectancy-1950-2017
  • Gneiting, Tilmann. 2011. “Making and Evaluating Point Forecasts.” Journal of the American Statistical Association 106 (494): 746–762. doi:10.1198/jasa.2011.r10138.
  • Greene, Kevin, Håvard Hegre, Frederick Hoyles, and Michael Colaresi. 2019. “Move It or Lose It: Introducing Pseudo-Earth Mover Divergence as a Context-Sensitive Metric for Evaluating and Improving Forecasting and Prediction Systems.” Paper presented at Barcelona School of Economics Summer Forum 2019, Barcelona, Spain, June 19.
  • Harris, Ian, Timothy J. Osborn, Phil Jones, and David Lister. 2020. “Version 4 of the CRU TS Monthly High-Resolution Gridded Multivariate Climate Dataset.” Scientific Data 7 (1): 1–18. doi:10.1038/s41597-020-0453-3.
  • Hastie, Trevor, Robert Tibshirani, and J. H. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. Springer Series in Statistics. New York: Springer.
  • Hegre, Håvard, Marie Allansson, Matthias Basedau, Michael Colaresi, Mihai Croicu, Hanne Fjelde, Frederick Hoyles, et al. 2019. “ViEWS: A Political Violence Early-Warning System.” Journal of Peace Research 56 (2): 155–174. doi:10.1177/0022343319823860.
  • Hegre, Håvard, Mihai Croicu, Kristine Eck, and Stina Högbladh. 2020. “Introducing the UCDP Candidate Events Dataset.” Research and Politics 7(3): 1–8.
  • Hegre, Håvard, Paola Vesco, and Michael Colaresi. 2022. “Lessons from an Escalation Prediction Competition.” International Interactions 48 (4): 000-000.
  • Hofste, Rutger Willem, Samantha Kuzma, Sara Walker, Edwin H. Sutanudjaja, Marc F.P. Bierkens, Marijn J.M. Kuijper, Marta Faneca Sanchez, Rens Van Beek, Yoshihide Wada, Sandra Galvis Rodrıǵuez, and Paul Reig. 2019. “Aqueduct 3.0: Updated Decision-Relevant Global Water Risk Indicators.” World Resources Institute. Accessed November 15, 2021. https://doi.org/10.46830/writn.18.00146
  • ISO. 1994. ISO 5725-1: Accuracy (Trueness and Precision) of Measurement Methods and Results. ISO. 1994. Accessed March 4, 2021. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/01/18/11833.html
  • Jain, Aarshay. 2016. “XGBoost Parameters | XGBoost Parameter Tuning.” Analytics Vidhya (blog), March 1, 2016. https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/.
  • Latham, John, Renato Cumani, Ilaria Rosati, and Mario Bloise. 2014. Global Land Cover Share (GLC-SHARE) Database Beta-Release Version 1.0-2014. Rome: FAO.
  • Lin, Lawrence I-Kuei. 1989. “A Concordance Correlation Coefficient to Evaluate Reproducibility.” Biometrics 45 (1): 255–268. doi:10.2307/2532051.
  • Menditto, Antonio, Marina Patriarca, and Bertil Magnusson. 2007. “Understanding the Meaning of Accuracy, Trueness and Precision.” Accreditation and Quality Assurance 12 (1): 45–47. doi:10.1007/s00769-006-0191-z.
  • Muchlinski, David, David Siroky, Jingrui He, and Matthew Kocher. 2016. “Comparing Random Forest with Logistic Regression for Predicting Class-Imbalanced Civil War Onset Data.” Political Analysis 24 (1): 87–103. doi:10.1093/pan/mpv024.
  • Pandit, Vedhas, and Björn Schuller. 2020. “The Many-to-Many Mapping Between the Concordance Correlation Coefficient and the Mean Square Error.” ArXiv:1902.05180 [Cs, Math, Stat], July. http://arxiv.org/abs/1902.05180.
  • Pérez-Hoyos, Ana, Felix Rembold, Hervé Kerdiles, and Javier Gallego. 2017. “Comparison of Global Land Cover Datasets for Cropland Monitoring.” Remote Sensing 9 (11): 1118. doi:10.3390/rs9111118.
  • Pinker, Steven. 2011. The Better Angels of Our Nature: The Decline of Violence in History and Its Causes. London: Penguin UK.
  • Shaver, Andrew, David B. Carter, and Tsering Wangyal Shawa. 2019. “Terrain Ruggedness and Land Cover: Improved Data for Most Research Designs.” Conflict Management and Peace Science 36 (2): 191–218. doi:10.1177/0738894216659843.
  • Smits, Jeroen, and Iñaki Permanyer. 2019. “The Subnational Human Development Database.” Scientific Data 6 (1): 1–5. doi:10.1038/sdata.2019.38.
  • Tollefsen, Andreas Forø, Håvard Strand, and Halvard Buhaug. 2012. “PRIO-GRID: A Unified Spatial Data Structure.” Journal of Peace Research 49 (2): 363–374. doi:10.1177/0022343311431287.
  • Vesco, Paola, Håvard Hegre, Michael Colaresi, Remco B. Jansen, Adeline Lo, Gregor Reisch, and Nils B. Weidmann 2022. “United They Stand: Findings from an Escalation Prediction Competition.” International Interactions 48 (4): 000–000.
  • Vogt, Manuel, Nils-Christian Bormann, Seraina Rüegger, Lars-Erik Cederman, Philipp Hunziker, and Luc Girardin. 2015. “Integrating Data on Ethnicity, Geography, and Conflict: The Ethnic Power Relations Data Set Family.” Journal of Conflict Resolution 59 (7): 1327–1342. doi:10.1177/0022002715591215.
  • Walter, Barbara F. 2009. “Bargaining Failures and Civil War.” Annual Review of Political Science 12 (1): 243–261. doi:10.1146/annurev.polisci.10.101405.135301.
  • Weidmann, Nils B., Doreen Kuse, and Kristian Skrede Gleditsch. 2010. “The Geography of the International System: The CShapes Dataset.” International Interactions 36 (1): 86–106. doi:10.1080/03050620903554614.
  • Wessel, Paal, and Walter H. F. Smith. 1996. “A Global, Self-Consistent, Hierarchical, High-Resolution Shoreline Database.” Journal of Geophysical Research: Solid Earth 101 (B4): 8741–8743. doi:10.1029/96JB00104.