Diseño de un modelo predictivo como apoyo de toma de decisiones en la relación entre soñador y voluntario de la Fundación Ambulancia Deseo
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2022-06
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Universidad de Guayaquil - Facultad de Ciencias Matemáticas y Físicas - Carrera de Ingeniería Civil
Resumen
La importancia de brindar apoyo a personas con enfermedades catastróficas es notaría cuando se conoce a profundidad de sus necesidades. Existiendo fundaciones como "Ambulancia Deseo" quien conoce el valor de brindar emociones positivas, generándolas, mediante el cumplimiento de sueños vivenciales a personas con enfermedades catastróficas, es ahí donde se logra comprender el valor significativo de ayudar a las fundaciones. Entre los múltiples desafíos que enfrenta la fundación “Ambulancia Deseo” se destaca la necesidad de relacionar adecuadamente el soñador y voluntario a la hora de cumplir un sueño. Así, este proyecto tiene como objetivo, en primer lugar, distinguir que factores influyen en la relación entre soñador y voluntario para el cumplimiento de un sueño. En segundo lugar, analizar las diferentes metodologías que son utilizadas en minería de datos, se dispuso que la metodología CRISP-DM proporciona las fases necesarias para el desarrollo de este trabajo. En las diferentes fases que brinda la metodología se analizaron los datos y paralelamente los métodos de machine Learning a utilizar, definiendo arboles de decisiones como el algoritmo seleccionado para el desarrollo de la propuesta por su simplicidad y eficacia.
The importance of providing support to people with catastrophic illnesses is evident when their needs are thoroughly understood. There are foundations such as "Desire Ambulance" who know the value of providing positive emotions, generating them, through the fulfillment of experiential dreams to people with catastrophic illnesses, that is where the significant value of helping foundations is understood. Among the multiple challenges faced by the "Desire Ambulance" foundation, the need to adequately relate the dreamer and the volunteer when it comes to fulfilling a dream stands out. Thus, this project aims, first of all, to distinguish which factors influence the relationship between dreamer and volunteer for the fulfillment of a dream. Second, to analyze the different methodologies that are used in data mining, it was established that the CRISP-DM methodology provides the necessary phases for the development of this work. In the different phases provided by the methodology, the data and, in parallel, the machine learning methods to be used were analyzed, defining decision trees as the algorithm selected for the development of the proposal due to its simplicity and effectiveness.
The importance of providing support to people with catastrophic illnesses is evident when their needs are thoroughly understood. There are foundations such as "Desire Ambulance" who know the value of providing positive emotions, generating them, through the fulfillment of experiential dreams to people with catastrophic illnesses, that is where the significant value of helping foundations is understood. Among the multiple challenges faced by the "Desire Ambulance" foundation, the need to adequately relate the dreamer and the volunteer when it comes to fulfilling a dream stands out. Thus, this project aims, first of all, to distinguish which factors influence the relationship between dreamer and volunteer for the fulfillment of a dream. Second, to analyze the different methodologies that are used in data mining, it was established that the CRISP-DM methodology provides the necessary phases for the development of this work. In the different phases provided by the methodology, the data and, in parallel, the machine learning methods to be used were analyzed, defining decision trees as the algorithm selected for the development of the proposal due to its simplicity and effectiveness.
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CATASTRÓFICA, POSITIVAS, FUNDACIONES, ALGORITMO, MINERÍA
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