Found 844 datasets matching "machine-learning".
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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: 214.23 | Views last month: 1 -
This dataset contains a comparison of packet loss counts vs handovers using four different methods: baseline, heuristic, distance, and machine learning, as well as the data used to train a machine...
Search relevance: 199.64 | Views last month: 6 -
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: 198.36 | 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: 190.00 | Views last month: 0 -
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: 188.35 | Views last month: 0 -
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive...
Search relevance: 178.25 | Views last month: 0 -
Supplementary data for "Tia Tate, Grace Patlewicz, Imran Shah, A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted...
Search relevance: 174.97 | Views last month: 0 -
Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring...
Search relevance: 174.43 | Views last month: 0 -
This is the geospatial and hydroclimate input data used to develop data-driven Machine Learning (ML) models as well as model estimated water quality based risk metrics and watershed health...
Search relevance: 173.90 | Views last month: 7 -
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir...
Search relevance: 173.79 | Views last month: 1 -
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: 171.91 | Views last month: 0 -
Data and code for "Dawson, D.E.; Lau, C.; Pradeep, P.; Sayre, R.R.; Judson, R.S.; Tornero-Velez, R.; Wambaugh, J.F. A Machine Learning Model to Estimate Toxicokinetic Half-Lives of Per- and...
Search relevance: 170.91 | 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: 169.74 | Views last month: 0 -
This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project....
Search relevance: 166.52 | Views last month: 0 -
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately...
Search relevance: 165.82 | Views last month: 0 -
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project. A...
Search relevance: 165.26 | Views last month: 1 -
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: 165.10 | Views last month: 0 -
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: 164.26 | Views last month: 0 -
CHIPS-FF (Computational High-Performance Infrastructure for Predictive Simulation-based Force Fields) is a universal, open-source benchmarking platform for machine learning force fields (MLFFs)....
Search relevance: 162.26 | Views last month: 2 -
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were...
Search relevance: 160.78 | Views last month: 2
