Found 24 datasets matching "gradient boosting".
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Water quality measurements at 3 beach sites in the Great Lakes from the summer of 2015: Edgewater Beach, OH; Grant Park, WI; Washington Park, MI. Data include associated environmental parameters...
Search relevance: 134.45 | Views last month: 1 -
A series of machine learning (ML) models were developed for Minnesota. The ML models were trained and tested using suspended sediment, bedload, streamflow, and geospatial data to predicted...
Search relevance: 84.54 | Views last month: 0 -
GeoTiff grids of models of prospectivity for clastic-dominated (CD) and Mississippi Valley-type (MVT) Pb-Zn mineralization for the US and Canada (combined) and Australia that used data provided in...
Search relevance: 71.91 | Views last month: 0 -
This child item dataset includes inputs to and outputs from an extreme gradient boosting model (XGBoost) to predict daily chlorophyll concentrations. Included in this dataset are the necessary...
Search relevance: 68.98 | Views last month: 0 -
This dataset provides estimates of forest aboveground biomass for three study areas and the entire Paragominas municipality, in Para, Brazil, in 2012. Aboveground biomass (in megagrams of carbon...
Search relevance: 64.57 | Views last month: 0 -
This dataset provides estimates of carbon dioxide (CO2) and methane (CH4) diffusive fluxes from waterbodies, and watershed landcover data for the central-interior of the Yukon-Kuskokwim Delta (YK...
Search relevance: 60.39 | Views last month: 0 -
Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016)
The Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) data set includes predictions of PM2.5 concentrations in grid cells at a resolution of 1 km...
Search relevance: 53.42 | Views last month: 0 -
The 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods data set models urban settlements in the Continental United States (CONUS) as of 2015. When...
Search relevance: 52.01 | Views last month: 3 -
Green and others (2021) developed a gradient boosted regression tree model to predict the mean groundwater age, or travel time, for shallow wells across a portion of the Great Lakes basin in the...
Search relevance: 50.65 | Views last month: 0 -
The Daily and Annual NO2 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000-2016) data set contains daily predictions of Nitrogen Dioxide (NO2) concentrations at a high...
Search relevance: 49.30 | Views last month: 0 -
This data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme...
Search relevance: 49.27 | Views last month: 9 -
This data release contains modeled daily chlorophyll concentration for 82 streams and rivers across the conterminous United States. Estimates of daily chlorophyll concentration were generated...
Search relevance: 48.58 | Views last month: 0 -
The Daily 8-Hour Maximum and Annual O3 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000 - 2016) data set contains estimates of ozone concentrations at a high resolution in...
Search relevance: 47.32 | Views last month: 0 -
This dataset contains data files of modeled top cover estimates by plant functional type (PFT) for the Arctic and Boreal Alaska and Yukon regions. Estimates are presented for single years at...
Search relevance: 47.32 | Views last month: 0 -
7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015)
This data release provides the data and R scripts used for the 2018 publication titled "Improving predictions of hydrological low-flow indices in ungaged basins using machine learning",...
Search relevance: 46.12 | Views last month: 0 -
The Supporting Information contains the following material: data set with ARN groups downloaded from https://echa.europa.eu/assessment-regulatory-needs in Feb 2023...
Search relevance: 45.71 | Views last month: 2 -
An extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in shallow groundwater across the conterminous United States (CONUS). Nitrate was...
Search relevance: 44.98 | Views last month: 0 -
A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in groundwater across the conterminous United States (CONUS)....
Search relevance: 43.33 | Views last month: 0 -
The Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, Version 1.10 (2000-2016) data set includes predictions of PM2.5 concentration in grid cells at a resolution...
Search relevance: 39.67 | Views last month: 0 -
An extreme gradient boosting ensemble tree model predicting per- and polyfluoroalkyl substances (PFAS) occurrence in groundwater at the depths typical of the bottom of public and domestic drinking...
Search relevance: 38.35 | Views last month: 5
