首页|Researchers at Dalhousie University Report New Data on Machine Learning (Filling the Gaps In Soil Data: a Multi-model Framework for Addressing Data Gaps Using P edotransfer Functions and Machine-learning With Uncertainty Estimates To Estimat e ...)
Researchers at Dalhousie University Report New Data on Machine Learning (Filling the Gaps In Soil Data: a Multi-model Framework for Addressing Data Gaps Using P edotransfer Functions and Machine-learning With Uncertainty Estimates To Estimat e ...)
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Investigators discuss new findings in Machine Learning. According to news originating from Truro, Canada, by NewsRx co rrespondents, research stated, "Legacy soil datasets are a valuable resource and should be used to the greatest extent possible. However, such datasets may be i ncomplete, and lack observations for every attribute, as the dataset may be comp iled from multiple studies." Funders for this research include Forest Innovation Program of the Canadian Wood Fibre Centre, Natural Resources Canada, British Columbia Ministry of Water and Land Resource Stewardship, Natural Sciences and Engineering Research Council of Canada (NSERC), John R. Evans Leaders Fund, Spanish Government.
TruroCanadaNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningDalhousie University
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