Examinando por Materia "Random Forest"
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Ítem Análisis predictivo del riesgo de default en microcrédito un enfoque de machine learning en sector financiero(Universidad EAFIT, 2024) Mendoza Trillos, Laura; Suárez Sierra, Biviana MarcelaÍtem Predicción de deserción de clientes en el mercado de seguros de transporte de carga en Estados Unidos mediante técnicas de Machine Learning : un caso de estudio(Universidad EAFIT, 2024) Uribe Durango, Víctor Ricardo; Almonacid Hurtado, Paula MaríaÍtem Predicción del precio del oro en el mercado spot y el tipo de cambio USD–COP para la optimización del rango de cobertura en derivados de las compañías exportadoras del sector minero(Universidad EAFIT, 2024) Gallego Panesso, Cristian Alexander; Almonacid Hurtado, Paula MaríaThis study addresses the implementation of various time series regression and machine learning models, such as: ARIMA, ARIMAX, SARIMA and Random Forests with the objective of accurately predicting the price of gold in the spot market and the USD–COP exchange rate. Precision in these predictions is crucial for export companies in the mining sector, as it allows them to establish optimal coverage ranges in the use of financial derivatives. Throughout the study, different machine learning algorithms were evaluated and compared, selecting those that provided the most accurate and consistent results. The findings offer a valuable tool for financial risk management and strategic decision making in the context of gold price volatility and exchange rate fluctuations. At the end of the study, it is indicated that the ARIMAX Rolling Forecast model applied in a parameterization (1,1,0) was the most accurate and consistent model over time for the price forecasts of both assets.Ítem The random forest machine learning model performs better in predicting drug repositioning using networks : systematic review and meta-analysis(Universidad EAFIT, 2024) García Marín, Darlyn Juranny; García Zea, Jerson Alexander; García Zea, Jerson AlexanderÍtem Transferencias monetarias y acceso a crédito : el caso del programa Ingreso Solidario en Colombia(Universidad EAFIT, 2024) Betancur Téllez, Sebastián; Álvarez Franco, Pilar Beatriz; Cruz Castañeda, Vivian