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Rough-set based learning methods: A case study to assess th..:
Ashrafi, Negin
Ashrafi, Negin. Rough-set based learning methods: A case study to assess the relationship between the clinical delivery of cannabinoid medicine for anxiety, depression, sleep, patterns and predictability; A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Applied Computer Science, University of Winnipeg. Winnipeg, Manitoba, Canada: University of Winnipeg, 2022. DOI:10.36939/ir.202208251500.. , 2022
Link:
https://hdl.handle.net/10680/2014
RT Journal T1
Rough-set based learning methods: A case study to assess the relationship between the clinical delivery of cannabinoid medicine for anxiety, depression, sleep, patterns and predictability
UL https://suche.suub.uni-bremen.de/peid=base-ftunivwinnipeg:oai:winnspace.uwinnipeg.ca:10680_2014&Exemplar=1&LAN=DE A1 Ashrafi, Negin PB University of Winnipeg YR 2022 K1 Rough Sets K1 Machine Learning K1 Rough-Fuzzy Sets K1 Granular Computing K1 Mental Health K1 Cannabinoid Medicine JF Ashrafi, Negin. Rough-set based learning methods: A case study to assess the relationship between the clinical delivery of cannabinoid medicine for anxiety, depression, sleep, patterns and predictability; A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Applied Computer Science, University of Winnipeg. Winnipeg, Manitoba, Canada: University of Winnipeg, 2022. DOI:10.36939/ir.202208251500. LK http://dx.doi.org/https://hdl.handle.net/10680/2014 DO https://hdl.handle.net/10680/2014 SF ELIB - SuUB Bremen
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