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Metrics for Evaluating Machine Learning Cloud Services

Machine Learning (ML) is nowadays being offered as a service by several cloud providers. Consumers require metrics to be able to evaluate and compare between multiple ML cloud services. There aren’t many established metrics that can be used specifically for these types of services. In this paper, the Goal-QuestionMetric paradigm is used to define a set of metrics applicable for ML cloud services. The metrics are created based on goals expressed by professionals who use or are interested in using these services. At the end, a questionnaire is used to evaluate the metrics based on two criteria: relevance and ease of use.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-37882
Date January 2017
CreatorsTataru, Augustin
PublisherTekniska Högskolan, Högskolan i Jönköping, JTH, Datateknik och informatik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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