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Semantic segmentation of land use and land cover for mapping agricultural activities
(University of Missouri--Columbia, 2023)
and corresponding labels, test the prediction accuracies to see any chance to improve the pipeline built to con- tribute to filling the gap of the data acquisition problems that happened in the land use and land cover analysis in the agricultural economics. Based...
Land valuation using an innovative model combining machine learning and spatial context
(University of Missouri--Columbia, 2023)
joint model can improve the value estimation. The study also identifies the factors that are most influential in driving these models. A geodatabase was created by calculating proximity and accessibility to key locations as well as integrating socio-economic...
Assessing the quality and distribution of news in local television and newspaper markets using data science methods
(University of Missouri--Columbia, 2023)
[EMBARGOED UNTIL 5/1/2024] Increasingly over the last two decades, U.S. newspapers have struggled with declining readership, decreasing revenues and competition from social media companies, among other challenges. More ...
Quantlyzer : an R package for automated exploratory and predictive data analysis
(University of Missouri--Columbia, 2023)
Machine learning (ML) and statistical algorithms have been significantly used in various applications, such as data classification, predictive regression, and feature selection. As the need for data-driven insights continues ...