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Showing 1 to 4 of 4 for “"Shapley Additive Explanation"”.

  1. A Diverse and Comprehensive Air Quality Modeling Analysis of Houston, Texas: How Will Changing Emissions, Industries, and Legislation Impact the Air and Human Health?

    … Random Forest machine learning interpreted by SHapley Additive exPlanation (SHAP). VOC and NOx data from the urban Milby Park and industrial Lynchburg Ferry sites were analyzed for the O3 seasons of 2017-2021. This revealed that NOx emissions suppress O3 formation in the NOx-saturated urban …

    houston Repository record for A Diverse and Comprehensive Air Quality Modeling Analysis of Houston, Texas: How Will Changing Emissions, Industries, and Legislation Impact the Air and Human Health? (opens in a new tab)

  2. Multi-label/multi-class Deep Learning Classification Of Spatiotemporal Data

    … Specificity metrics. In the last study, model explanation is performed using Shapley Additive Explanation (SHAP) values and plotting them on an image-like background, a representation of the fNIRS channel layout used as data input. Overall, promising findings support the use of this approach in …

    syracuse-diss Repository record for Multi-label/multi-class Deep Learning Classification Of Spatiotemporal Data (opens in a new tab)

  3. Multi-Label/Multi-Class Deep Learning Classification of Spatiotemporal Data

    … Specificity metrics. In the last study, model explanation is performed using Shapley Additive Explanation (SHAP) values and plotting them on an image-like background, a representation of the fNIRS channel layout used as data input. Overall, promising findings support the use of this approach in …

    syracuse-diss Repository record for Multi-Label/Multi-Class Deep Learning Classification of Spatiotemporal Data (opens in a new tab)