首页|New Machine Learning Study Findings Recently Were Reported by Researchers at Aristotle University of Thessaloniki (Truthful Meta- explanations for Local Interpretability of Machine Learning Models)
New Machine Learning Study Findings Recently Were Reported by Researchers at Aristotle University of Thessaloniki (Truthful Meta- explanations for Local Interpretability of Machine Learning Models)
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Investigators publish new report on Machine Learning. According to news reporting from Thessaloniki, Greece, by NewsRx journalists, research stated, "Automated Machine Learning-based systems' integration into a wide range of tasks has expanded as a result of their performance and speed. Although there are numerous advantages to employing ML-based systems, if they are not interpretable, they should not be used in critical or high-risk applications." Funders for this research include HEAL-Link Greece, European Union (EU). The news correspondents obtained a quote from the research from the Aristotle University of Thessa- loniki, "To address this issue, researchers and businesses have been focusing on finding ways to improve the explainability of complex ML systems, and several such methods have been developed. Indeed, there are so many developed techniques that it is difficult for practitioners to choose the best among them for their applications, even when using evaluation metrics. As a result, the demand for a selection tool, a meta-explanation technique based on a high-quality evaluation metric, is apparent. In this paper, we present a local meta-explanation technique which builds on top of the truthfulness metric, which is a faithfulness-based metric."
ThessalonikiGreeceEuropeCyborgsEmerging TechnologiesMachine LearningAristotle University of Thessaloniki
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Springer Nature
