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).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
]
|
| contactPoint |
{
"fn": "Kristin Isaacs",
"hasEmail": "mailto:isaacs.kristin@epa.gov"
}
|
| describedBy | https://pasteur.epa.gov/uploads/486/documents/read_me_metadata.docx |
| describedByType | application/vnd.openxmlformats-officedocument.wordprocessingml.document |
| description | 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). |
| distribution |
[
{
"title": "ranksfunctionimp.csv",
"mediaType": "application/vnd.ms-excel",
"downloadURL": "https://pasteur.epa.gov/uploads/486/ranksfunctionimp.csv"
}
]
|
| identifier | A-mpgn-486 |
| keyword |
[
"ExpoCast",
"Exposure modeling",
"chemical function",
"chemical prioritization",
"consumer products",
"cosmetics",
"machine learning"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2016-08-05 |
| programCode |
[
"020:095"
]
|
| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
}
}
}
|
| references |
[
"https://doi.org/10.1016/j.toxrep.2016.08.011"
]
|
| rights |
null
|
| title | Importance of predictor variables for models of chemical function |
