{
    "identifier": "ark:\/88434\/mds2-2953",
    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Peter Fontana"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2953",
    "title": "Towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) MIg analyZeR (mizr) Package",
    "description": "Our work towards a Structured Evaluation Methodology for Artificial Intelligence Technology (SEMAIT) aims to provide plots, tools, methods, and strategies to extract insights out of various machine learning (ML) and Artificial Intelligence (AI) data.Included in this software is the MIg analyZeR (mizr) R software package that produces various plots. It was initially developed within the Multimodal Information Group (MIG) at the National Institute of Standards and Technology (NIST).This software is documented, configured to be installed as an R package, and comes with an example SEMAIT script with an example (system, dataset, metrics, score) ML tuple set that we constructed ourselves.",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "accessURL": "https:\/\/github.com\/usnistgov\/semait_mizr",
            "format": "GitHub repository",
            "description": "Access URL",
            "title": "GitHub Access URL"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2023-03-10 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": [
        "Mathematics and Statistics:Statistical analysis",
        "Information Technology:Computational science"
    ],
    "keyword": [
        "analysis software",
        "artificial intelligence",
        "machine learning",
        "design of experiments"
    ]
}