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Developing a machine learning model to map new-build gentrification: A mixed-methods approach

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Published in:PLOS ONE
Format: Online Article RSS Article
Published: 2026
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container_title PLOS ONE
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discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
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genre Journal Article
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institution FRELIP
journal_source_facet PLOS ONE
publishDate 2026
publishDateSort 2026
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spellingShingle Developing a machine learning model to map new-build gentrification: A mixed-methods approach
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
subject_facet Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
title Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_auth Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_full Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_fullStr Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_full_unstemmed Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_short Developing a machine learning model to map new-build gentrification: A mixed-methods approach
title_sort developing a machine learning model to map new-build gentrification: a mixed-methods approach
topic Cybersecurity, Cryptography and Privacy
Computer Science & IT
Engineering & Technology
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0341844