Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning

El objetivo de este trabajo es estudiar los patrones espaciales de delitos a través de la implementación de técnicas de machine learning, para predecir la probabilidad de ocurrencia de diversos tipos de crímenes a nivel anual con diferencias espaciales en Medellín, Colombia, a partir de datos histór...

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Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
spa
OAI Identifier:
oai:repository.urosario.edu.co:10336/41887
Acceso en línea:
https://repository.urosario.edu.co/handle/10336/41887
Palabra clave:
Machine Learning
Variables socioeconómicas
Patrones espaciales
Machine learning
Crime patterns
Classification models
Crime prediction
Crime analysis
Public politics
Socioeconomic variables
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Attribution-NonCommercial-NoDerivatives 4.0 International
id EDOCUR2_f13070ef736f628946799118b70108e6
oai_identifier_str oai:repository.urosario.edu.co:10336/41887
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.none.fl_str_mv Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
dc.title.TranslatedTitle.none.fl_str_mv Crime and Economic Factors in Medellín: A Prediction Study with Machine Learning
title Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
spellingShingle Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
Machine Learning
Variables socioeconómicas
Patrones espaciales
Machine learning
Crime patterns
Classification models
Crime prediction
Crime analysis
Public politics
Socioeconomic variables
title_short Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
title_full Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
title_fullStr Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
title_full_unstemmed Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
title_sort Crimen y factores económicos en Medellín: un estudio de predicción con Machine Learning
dc.contributor.advisor.none.fl_str_mv García Suaza, Andrés Felipe
dc.subject.none.fl_str_mv Machine Learning
Variables socioeconómicas
Patrones espaciales
topic Machine Learning
Variables socioeconómicas
Patrones espaciales
Machine learning
Crime patterns
Classification models
Crime prediction
Crime analysis
Public politics
Socioeconomic variables
dc.subject.keyword.none.fl_str_mv Machine learning
Crime patterns
Classification models
Crime prediction
Crime analysis
Public politics
Socioeconomic variables
description El objetivo de este trabajo es estudiar los patrones espaciales de delitos a través de la implementación de técnicas de machine learning, para predecir la probabilidad de ocurrencia de diversos tipos de crímenes a nivel anual con diferencias espaciales en Medellín, Colombia, a partir de datos históricos y sociodemográficos.
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-12-13T17:10:28Z
dc.date.available.none.fl_str_mv 2023-12-13T17:10:28Z
dc.date.created.none.fl_str_mv 2023-12-12
dc.type.none.fl_str_mv bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.document.none.fl_str_mv Trabajo de grado
dc.type.spa.none.fl_str_mv Trabajo de grado
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/41887
url https://repository.urosario.edu.co/handle/10336/41887
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.none.fl_str_mv Abierto (Texto Completo)
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
Abierto (Texto Completo)
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.none.fl_str_mv 40 pp
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad del Rosario
dc.publisher.department.spa.fl_str_mv Facultad de Economía
dc.publisher.program.spa.fl_str_mv Maestría en Economía
institution Universidad del Rosario
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spelling García Suaza, Andrés Felipe8063566600Ardila Chávarro, María CamilaMagíster en EconomíaMaestríaFull timed6025f67-1ed2-4b65-bd93-dd2dd1afda17-12023-12-13T17:10:28Z2023-12-13T17:10:28Z2023-12-12El objetivo de este trabajo es estudiar los patrones espaciales de delitos a través de la implementación de técnicas de machine learning, para predecir la probabilidad de ocurrencia de diversos tipos de crímenes a nivel anual con diferencias espaciales en Medellín, Colombia, a partir de datos históricos y sociodemográficos.Criminal activity negatively affects people's quality of life and economic progress. Given the advance in economic research, which leverages machine learning to detect patterns and analyze trends in specific fields, these techniques are being used in various contexts, including crime prevention. The objective of this work is to study the spatial patterns of crimes through the implementation of machine learning techniques, to predict the probability of occurrence of various types of crimes at an annual level with spatial differences in Medellín, Colombia, based on historical data. and sociodemographic. To carry out this objective, the Ordinary Least Squares, Random Forest and Extreme Gradient Boosting models were used, which obtained acceptable levels of performance, given their high precision. A relevant result is that the socioeconomic variables related to the proportion of men, people between 16 and 30 years of age, proportion of unemployed people, people who belong to SISBEN, proportion of people with multidimensional poverty, proportion of people with quantitative deficit of housing and who are part of socioeconomic stratum 1 or 2, both at the neighborhood and grid level had a high predictive power. For the purpose of this research, this will be used in decision-making and the formulation of public policies aimed at reducing crime.40 ppapplication/pdfhttps://repository.urosario.edu.co/handle/10336/41887spaUniversidad del RosarioFacultad de EconomíaMaestría en EconomíaAttribution-NonCommercial-NoDerivatives 4.0 InternationalAbierto (Texto Completo)EL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma. PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe. EL AUTOR, autoriza a LA UNIVERSIDAD DEL ROSARIO, para que en los términos establecidos en la Ley 23 de 1982, Ley 44 de 1993, Decisión andina 351 de 1993, Decreto 460 de 1995 y demás normas generales sobre la materia, utilice y use la obra objeto de la presente autorización. -------------------------------------- POLITICA DE TRATAMIENTO DE DATOS PERSONALES. Declaro que autorizo previa y de forma informada el tratamiento de mis datos personales por parte de LA UNIVERSIDAD DEL ROSARIO para fines académicos y en aplicación de convenios con terceros o servicios conexos con actividades propias de la academia, con estricto cumplimiento de los principios de ley. 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No. 5; pp. 99-113 : Facultad Latinoamericana de Ciencias Sociales (FLACSO), Sede Ecuador;Cornish, Derek B; Clarke, Ronald V (2016) The rational choice perspective. pp. 48-80 : Routledge;Cornish, Derek B; Clarke, Ronald V (1989) Crime specialisation, crime displacement and rational choice theory. pp. 103-117 : Springer;instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURMachine LearningVariables socioeconómicasPatrones espacialesMachine learningCrime patternsClassification modelsCrime predictionCrime analysisPublic politicsSocioeconomic variablesCrimen y factores económicos en Medellín: un estudio de predicción con Machine LearningCrime and Economic Factors in Medellín: A Prediction Study with Machine LearningbachelorThesisTrabajo de gradoTrabajo de gradohttp://purl.org/coar/resource_type/c_7a1fFacultad de EconomíaORIGINALCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdfCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdfapplication/pdf3434471https://repository.urosario.edu.co/bitstreams/3e4db522-c4d6-40cb-9eab-a52dd777874b/download783f167c74ed784f814b335bbdc2521bMD51references.risreferences.risapplication/x-research-info-systems43508https://repository.urosario.edu.co/bitstreams/5baf5d55-b87e-4b34-b862-1308274c6846/download50662d0d217f53055794a2b8ed1a886fMD53LICENSElicense.txtlicense.txttext/plain1483https://repository.urosario.edu.co/bitstreams/33cd2236-edfb-4d7a-9fd7-866c26fdd725/downloadb2825df9f458e9d5d96ee8b7cd74fde6MD52CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8899https://repository.urosario.edu.co/bitstreams/a46708ec-6b4c-4ee3-b379-bed7f9b8e343/download3b6ce8e9e36c89875e8cf39962fe8920MD54TEXTCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdf.txtCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdf.txtExtracted texttext/plain99962https://repository.urosario.edu.co/bitstreams/43e04561-6479-4294-90bf-dd299c35c4e5/download7529e1cdff763d609fb3f25f934f6b78MD55THUMBNAILCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdf.jpgCrimen_y_Factores_Economicos_en_Medellin_Un_Estudio_de_Prediccion_con_Machine_Learning.pdf.jpgGenerated Thumbnailimage/jpeg2615https://repository.urosario.edu.co/bitstreams/26924378-5d82-459a-aa9a-efd7245206b2/downloade29becb03211cd80d0afeade77b1a410MD5610336/41887oai:repository.urosario.edu.co:10336/418872023-12-14 03:01:35.738http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttps://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.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