Found 244 datasets matching "machine learning models".
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The open dataset, software, and other files accompanying the manuscript "An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty...
Search relevance: 251.37 | Views last month: 0 -
ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models
This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using...
Search relevance: 204.28 | Views last month: 0 -
This model archive contains the input data, model code, and model outputs for machine learning models that predict daily non-tidal stream salinity (specific conductance) for a network of 459...
Search relevance: 192.12 | Views last month: 0 -
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: 162.93 | Views last month: 0 -
Data and preliminary machine-learning models used to predict manganese and 1,4-dioxane in groundwater on Long Island are documented in this data release. Concentration data used to develop the...
Search relevance: 154.21 | Views last month: 1 -
Due to the increasing diversity of organic contaminants discharged into anoxic water environments, reactivity prediction is necessary for chemical persistence evaluation for water treatment and...
Search relevance: 146.28 | Views last month: 1 -
This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The...
Search relevance: 128.22 | Views last month: 0 -
The dataset include hydroclimate and ambient environmental as the input data and Cyanobacterial HABs Index (CI) calculated from satellite imageries as the output data altogether used to train and...
Search relevance: 121.97 | Views last month: 5 -
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission...
Search relevance: 92.04 | Views last month: 0 -
Real-time, image-based monitoring for stored product insect pests could increase timely treatments and protection for postharvest products throughout the supply chain. Artificial intelligence (AI)...
Search relevance: 87.23 | Views last month: 1 -
High-resolution elevation data provide a foundational layer needed to understand regional hydrology and ecology under contemporary and future-predicted conditions with accelerated sea-level rise....
Search relevance: 85.65 | Views last month: 0 -
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany...
Search relevance: 84.47 | Views last month: 0 -
This paper is a progress report of an effort whose goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently,...
Search relevance: 80.50 | Views last month: 0 -
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the...
Search relevance: 79.69 | Views last month: 1 -
A code repository and accompanying data for incorporating imperfect theory into machine learning for improved prediction and explainability. Specifically, it focuses on the case study of the...
Search relevance: 79.68 | Views last month: 1 -
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: 78.93 | Views last month: 3 -
Results from generalized additive models (GAM), random forest models (RFM), and cubist models (CUB) for three Dauphin Island Sealab (DIS) operated salinity sites in Mobile Bay are reported in this...
Search relevance: 78.53 | Views last month: 0 -
This data release contains one dataset and one model archive in support of the journal article "Leveraging machine learning to automate regression model evaluations for large multi-site...
Search relevance: 78.31 | Views last month: 2 -
The data are comprised of input and output data from Machine Learning models that were developed to predict watershed health (WH) values in HUC-10 sub-watersheds within three major Midwest river...
Search relevance: 77.68 | Views last month: 1 -
Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art...
Search relevance: 77.28 | Views last month: 1
