Importance of predictor variables for models of chemical function

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).

Data and Resources

Additional Info

Field Value
Source https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B60EBA274-914A-4B59-8D2E-763C6BF391F6%7D
Version
Author
Author Email
Maintainer
Maintainer Email
Shared (this field will be removed in the future) Open
IB1 Sensitivity Class
IB1 Trust Framework
IB1 Dataset Assurance
IB1 Trust Framework
GUID A-mpgn-486
Language
dcat_modified 2016-08-05
dcat_publisher_name U.S. EPA Office of Research and Development (ORD)
ib1_trust_framework []