首页|Researchers from University of Florida Report Findings in Machine Learning (Anal yzing Spatial Heterogeneity of Ridesourcing Usage Determinants Using Explainable Machine Learning)
Researchers from University of Florida Report Findings in Machine Learning (Anal yzing Spatial Heterogeneity of Ridesourcing Usage Determinants Using Explainable Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Machine Learning. According to news reporting out of Gainesville, Florida, by News Rx editors, research stated, “There is a pressing need to study spatial heteroge neity of ridesourcing usage determinants to develop bettertargeted transportatio n and land use policies. This study incorporates spatial information (i.e., the geographic coordinates of census tracts) into the machine learning model and lev erages state-of-the-art explainable machine learning techniques to analyze censu s-tract-to-census-tract ridesourcing usage, identify the key factors that shape the usage, and explore their nonlinear associations across different spatial con texts.”
GainesvilleFloridaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Florida
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