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NIST · ИТ · 0601f624b7645a03db51

0601f624b7645a03db51 · Effectiveness of dataset reduction in testing machine learning algorithms

Effectiveness of dataset reduction in testing machine learning algorithms

Abstract— Many machine learning algorithms examine large amounts of data to discover insights from hidden patterns. Testing these algorithms can be expensive and time-consuming. There is a need to speed up the testing process, especially in an agile

Официальный источник · 2020-08-25

Полные импортированные сведения карточки
{
  "title_en": "Effectiveness of dataset reduction in testing machine learning algorithms",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2020-08-25",
  "date_original": "August 25, 2020",
  "url": "https://www.nist.gov/publications/effectiveness-dataset-reduction-testing-machine-learning-algorithms",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Raghu N. Kacker , David R. Kuhn",
  "abstract_excerpt_en": "Abstract— Many machine learning algorithms examine large amounts of data to discover insights from hidden patterns. Testing these algorithms can be expensive and time-consuming. There is a need to speed up the testing process, especially in an agile",
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  "sources": [
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    {
      "title_en": "Effectiveness of dataset reduction in testing machine learning algorithms",
      "designation": "",
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      "status": "",
      "date": "2020-08-25",
      "date_original": "August 25, 2020",
      "url": "https://www.nist.gov/publications/effectiveness-dataset-reduction-testing-machine-learning-algorithms",
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      "display_en": "",
      "authors_en": "Raghu N. Kacker , David R. Kuhn",
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