Importance of predictor variables for models of chemical function

Metadata Updated: September 14, 2018

Importance of random forest predictors for all classification models of chemical function.

This dataset is associated with the following publication: Isaacs , K., M. Goldsmith, P. Egeghy , K. Phillips, R. Brooks, T. Hong, and J. Wambaugh. Characterization and prediction of chemical functions and weight fractions in consumer products. Toxicology Reports. Elsevier B.V., Amsterdam, NETHERLANDS, 3: 723-732, (2016).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources

References

http://dx.doi.org/10.1016/j.toxrep.2016.08.011

Dates

Metadata Created Date June 4, 2017
Metadata Updated Date September 14, 2018

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date June 4, 2017
Metadata Updated Date September 14, 2018
Publisher U.S. EPA Office of Research and Development (ORD)
Unique Identifier A-mpgn-486
Maintainer
Kristin Isaacs
Maintainer Email
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Data Dictionary https://pasteur.epa.gov/uploads/A-mpgn/486/documents/read_me_metadata.docx
Data Dictionary Type application/vnd.openxmlformats-officedocument.wordprocessingml.document
Harvest Object Id a9ac7ab5-e607-4b12-bf6b-474d24476892
Harvest Source Id cf9b0004-f9fd-420e-bade-a86839e82acf
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Data Last Modified 2016-08-05
Program Code 020:095
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents http://dx.doi.org/10.1016/j.toxrep.2016.08.011
Source Datajson Identifier True
Source Hash f2f8a85b0d51f2c6d887f396bd69cd9a14017422
Source Schema Version 1.1

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