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 bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "David Sheen",
"hasEmail": "mailto:david.sheen@nist.gov"
}
|
| description | 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 bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work. |
| distribution |
[
{
"title": "DOI Access for ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models",
"accessURL": "https://doi.org/10.18434/M32120"
},
{
"title": "Machine Learning Uncertainty Estimation Toolbox",
"format": "Python scripts and Jupyter notebooks",
"accessURL": "https://pages.nist.gov/ml_uncertainty_py/",
"description": "This software is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work."
}
]
|
| identifier | ark:/88434/mds2-2120 |
| issued | 2020-01-21 |
| keyword |
[
"machine learning",
"model calibration",
"uncertainty analysis"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-2120 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2019-06-10 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| references |
[
"http://dx.doi.org/10.1080/1062936X.2016.1238010",
"https://doi.org/10.1007/s00216-018-1240-2"
]
|
| theme |
[
"Information Technology:Data and informatics",
"Mathematics and Statistics:Numerical methods and software",
"Mathematics and Statistics:Uncertainty quantification"
]
|
| title | ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models |
