首页|New Findings from City University of Hong Kong Describe Advances in Machine Lear ning (Validating Unsupervised Machine Learning Techniques for Software Defect Pr ediction With Generic Metamorphic Testing)
New Findings from City University of Hong Kong Describe Advances in Machine Lear ning (Validating Unsupervised Machine Learning Techniques for Software Defect Pr ediction With Generic Metamorphic Testing)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in artificial intelligence. According to news reportingfrom Hong Kong, People’s Re public of China, by NewsRx journalists, research stated, “In the realm ofsoftwa re defect prediction, unsupervised models often step in when labelled datasets a re scarce, despitefacing the challenge of validating models without prior knowl edge of data. Addressing this, we proposed anovel approach leveraging generic m etamorphic testing to validate such models effectively, bypassing theneed for e xpert-derived metamorphic relations.”
City University of Hong KongHong KongPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learn ingSoftware
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