Citas bibligráficas
Escobedo, M., Tapia, C. (2024). Comparativa de modelos de regresión a fin de predecir el crimen en zonas de alto riesgo de la ciudad de Lima [Universidad de Lima]. https://hdl.handle.net/20.500.12724/21714
Escobedo, M., Tapia, C. Comparativa de modelos de regresión a fin de predecir el crimen en zonas de alto riesgo de la ciudad de Lima []. PE: Universidad de Lima; 2024. https://hdl.handle.net/20.500.12724/21714
@misc{renati/1439724,
title = "Comparativa de modelos de regresión a fin de predecir el crimen en zonas de alto riesgo de la ciudad de Lima",
author = "Tapia Aquino, Cynthia Lizet",
publisher = "Universidad de Lima",
year = "2024"
}
In Metropolitan Lima, Peru, crime is still an issue that has an impact on society. The purpose of this paper is to examine property crimes and acknowledge the paucity of research on their predictiveness. Regression approaches including Extra Tree, XGBoost, Bag, AdaBoost, Support Vector, and Random Forest are utilized to overcome this issue. The study outcomes are enhanced by optimizing the hyperparameters with GridSearchCV. Error measures including mean absolute error (MAE), root mean square error (RMSE), and root mean square error (MSE) are assessed for the Extra Tree Regression model, which has a coefficient of determination (R2) of 0.79. This strategy resolves ambiguity and counteracts citizen uneasiness by taking temporal trends of crime into account.
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