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Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts
dc.contributor.author | Escobedo Neyra, María Cielo | |
dc.contributor.author | Tapia Aquino, Cynthia, Lizet | |
dc.contributor.author | Gutiérrez Cárdenas, Juan Manuel | |
dc.contributor.author | Ayma, Víctor | |
dc.contributor.other | Gutiérrez Cárdenas, Juan Manuel | |
dc.date.accessioned | 2024-04-19T13:54:31Z | |
dc.date.available | 2024-04-19T13:54:31Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Escobedo, M., Tapia, C., Gutierrez, J., & Ayma, V. (2024). Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts. International Journal of Advanced Computer Science and Applications. https://doi.org/10.14569/IJACSA.2024.0150307. | es_PE |
dc.identifier.issn | 2156-5570 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12724/20201 | |
dc.description.abstract | Crime continues to be an issue, in Metropolitan Lima, Peru affecting society. Our focus is on property crimes. We recognized the lack of studies on predicting these crimes. To tackle this problem, we used regression techniques such as XGBoost, Extra Tree, Support Vector, Bagging, Random Forest and AdaBoost. Through GridsearchCV we optimized hyperparameters to enhance our research findings. The results showed that Extra Tree Regression stood out as the model with an R2 value of 0.79. Additionally, error metrics like MSE (185.43) RMSE (13.62) and MAE (10.47) were considered to evaluate the model's performance. Our approach considers time patterns in crime incidents. Contributes, to addressing the issue of insecurity in a meaningful way. © (2024), (Science and Information Organization). All Rights Reserved. | en_EN |
dc.format | es_PE | |
dc.language.iso | eng | es_PE |
dc.publisher | Science and Information Organization | en_EN |
dc.relation.ispartof | urn:issn:2156-5570 | |
dc.rights | open access | |
dc.source | Repositorio Institucional - Ulima | es_PE |
dc.source | Universidad de Lima | es_PE |
dc.subject | pendiente | es_PE |
dc.title | Comparing Regression Models to Predict Property Crime in High-Risk Lima Districts | en_EN |
dc.type | info:eu-repo/semantics/article | |
dc.type.other | Artículo en Scopus | es_PE |
dc.identifier.journal | International Journal of Advanced Computer Science and Applications | en_EN |
dc.publisher.country | GB | es_PE |
dc.description.peer-review | Revisión por pares | es_PE |
dc.subject.ocde | pendiente | |
dc.identifier.doi | https://doi.org/10.14569/IJACSA.2024.0150307 | |
ulima.lineadeinvestigacion | pendiente | es_PE |
dc.contributor.student | Escobedo Neyra, María Cielo (Ingeniería de Sistemas) | |
dc.contributor.student | Tapia Aquino, Cynthia, Lizet (Ingeniería de Sistemas) | |
ulima.cat | OI | |
ulima.autor.afiliacion | pendiente | |
ulima.autor.carrera | pendiente | |
dc.identifier.scopusid | 2-s2.0-85189935904 |
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