{"@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": ["006:55"], "contactPoint": {"fn": "Peter Fontana", "hasEmail": "mailto:peter.fontana@nist.gov"}, "description": "This software repository contains a python package Aegis (Active Evaluator Germane Interactive Selector) package that allows us to evaluate machine learning systems's performance (according to a metric such as accuracy) by adaptively sampling trials to label from an unlabeled test set to minimize the number of labels needed. This includes sample (public) data as well as a simulation script that tests different label-selecting strategies on already labelled test sets. This software is configured so that users can add their own data and system outputs to test evaluation.", "distribution": [{"accessURL": "https://doi.org/10.18434/M32227", "title": "DOI Access for Active Evaluation Software for Selection of Ground Truth Labels"}], "identifier": "ark:/88434/mds2-2227", "issued": "2020-07-09", "keyword": ["active evaluation", "ar", "machine learning"], "landingPage": "https://github.com/usnistgov/active-evaluation", "language": ["en"], "license": "https://www.nist.gov/open/license", "modified": "2020-04-28 00:00:00", "programCode": ["006:045"], "publisher": {"@type": "org:Organization", "name": "National Institute of Standards and Technology"}, "theme": ["Information Technology:Data and informatics"], "title": "Active Evaluation Software for Selection of Ground Truth Labels"}