Lifecycle Models in Machine Learning Development

Crespí, A.; Mesquida, A.-L.; Monserrat, M.; Mas, A.

dc.contributor.author	Crespí, A.
dc.contributor.author	Mesquida, A.-L.
dc.contributor.author	Monserrat, M.
dc.contributor.author	Mas, A.
dc.date.accessioned	2025-05-27T12:21:29Z
dc.identifier.citation	Crespí, A., Mesquida, A.-L., Monserrat, M. i Mas, A. (2025). Lifecycle Models in Machine Learning Development. Expert Systems, 42(4). https://doi.org/10.1111/exsy.70029	ca
dc.identifier.uri	http://hdl.handle.net/11201/170326
dc.description.abstract	[eng] Machine Learning (ML) development introduces challenges that traditional software processes often struggle to address. As ML applications grow in complexity and adoption, various lifecycle models have been proposed to address the unique stages of ML development. This study systematically synthesises these models, mapping their stages and activities to provide an understand-ing of the ML development landscape. The findings highlight research gaps and opportunities, offering insights for advancing academic research and practical implementation.	en
dc.format	application/pdf	en
dc.publisher	Wiley
dc.relation.ispartof	Expert Systems, 2025, vol. 42, num.4
dc.rights	all rights reserved
dc.subject.classification	004 - Informàtica	ca
dc.subject.other	004 - Computer Science and Technology. Computing. Data processing	en
dc.title	Lifecycle Models in Machine Learning Development	en
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Article
dc.date.updated	2025-05-27T12:21:29Z
dc.date.embargoEndDate	info:eu-repo/date/embargoEnd/2100-01-01
dc.embargo	2100-01-01
dc.rights.accessRights	info:eu-repo/semantics/closedAccess
dc.identifier.doi	https://doi.org/10.1111/exsy.70029