Monday, February 18, 2019

Statistician raises red flag about reliability of machine learning techniques | Digital Trends

Actual results may vary... Also see AAAS: Machine learning 'causing science crisis' | BBC
"Dr Genevera Allen, associate professor of statistics, computer science, and electrical and computer engineering Rice University in Houston, Texas has discussed this topic at a press briefing and at a scientific conference, the 2019 Annual Meeting of the American Association for the Advancement of Science (AAAS). She warned that researchers in the field of machine learning have spent so much time developing predictive models that they have not devoted enough attention to checking the accuracy of their models, and that the field must develop systems which can assess the accuracy of their own findings.

“The question is, ‘Can we really trust the discoveries that are currently being made using machine-learning techniques applied to large data sets?'” Allen said in a statement. “The answer in many situations is probably, ‘Not without checking,’ but work is underway on next-generation machine-learning systems that will assess the uncertainty and reproducibility of their predictions.”"
Statistician raises red flag about reliability of machine learning techniques | Digital Trends

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