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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 <Title>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</Title>

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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