bdda68ce55e108bf1896 · Combinatorial Testing Metrics for Machine Learning
Combinatorial Testing Metrics for Machine Learning
This short paper defines a combinatorial coverage metric for comparing machine learning (ML) data sets and proposes the differences between data sets as a function of combinatorial coverage. The paper illustrates its utility for evaluating and predicting
{
"title_en": "Combinatorial Testing Metrics for Machine Learning",
"designation": "",
"series": "",
"status": "",
"date": "2021-04-12",
"date_original": "April 12, 2021",
"url": "https://www.nist.gov/publications/combinatorial-testing-metrics-machine-learning",
"source": "NIST Publications",
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"authors_en": "Erin Lanus, Laura Freeman, D. Richard Kuhn , Raghu N. Kacker",
"abstract_excerpt_en": "This short paper defines a combinatorial coverage metric for comparing machine learning (ML) data sets and proposes the differences between data sets as a function of combinatorial coverage. The paper illustrates its utility for evaluating and predicting",
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{
"title_en": "Combinatorial Testing Metrics for Machine Learning",
"designation": "",
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"date": "2021-04-12",
"date_original": "April 12, 2021",
"url": "https://www.nist.gov/publications/combinatorial-testing-metrics-machine-learning",
"source": "NIST Publications",
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"authors_en": "Erin Lanus, Laura Freeman, D. Richard Kuhn , Raghu N. Kacker",
"abstract_excerpt_en": "This short paper defines a combinatorial coverage metric for comparing machine learning (ML) data sets and proposes the differences between data sets as a function of combinatorial coverage. The paper illustrates its utility for evaluating and predicting"
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