University of California Researcher Reports Research in Machine Learning (Enhancing the Detection of Social Desirability Bias Using Machine Learning: A Novel Ap plication of Person-Fit Indices)
University of California Researcher Reports Research in Machine Learning (Enhancing the Detection of Social Desirability Bias Using Machine Learning: A Novel Ap plication of Person-Fit Indices)
加州大学研究人员报告了机器学习的研究(使用机器学习加强对社会期望偏差的检测：个人匹配指数的新应用)
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摘要
由机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑-调查人员讨论人工智能的新发现。根据NewsRx编辑在La Jolla,United Sta Tes的新闻报道，研究表明，"社会期望偏差(SDB)是对量表或调查答复结论有效性的共同威胁"。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting out of La Jolla, United Sta tes, by NewsRx editors, research stated, “Social desirability bias (SDB) is a co mmon threat to the validity of conclusions from responses to a scale or survey.”
Key words
University of California/La Jolla/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning
NETL
NSTL