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A Machine Learning Approach To Crime Investigation In The New York City Land Area
Malmö University, Faculty of Technology and Society (TS).
2020 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This dissertation will speci cally discuss how machine learning, through some of its algorithms, is able to investigate the various kinds of crime committed in the New York City land area, with special focus on the root-cause, allegedly paving the way for the violation of certain areas of the law. After covering some general background information concerning the history of this eld while discussing a few examples taken from previous work, as well as the history of crime within the interested geographical area, focus will be placed in rst of all nding ways to retrieve all the necessary numerical information dating back several years, since some of them might not be explicitly available, and after ful lling this task, the selected machine learning algorithms will be implemented to have an insight about the relationship between the chosen variables. We then conclude with the direction in which future research should be heading.

Place, publisher, year, edition, pages
Malmö universitet/Teknik och samhälle , 2020.
Keywords [en]
Machine learning, Crime
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-20411Local ID: 32553OAI: oai:DiVA.org:mau-20411DiVA, id: diva2:1480286
Educational program
TS Computer Science, Master Programme
Supervisors
Examiners
Available from: 2020-10-27 Created: 2020-10-27Bibliographically approved

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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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