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    Improve the Daily Societal Operations Using Credit Fraud Detection: A Big Data Classification Solution

    Credit fraud detectionCredit fraud detection grows rapidly with the development of electronic payment. It is part of the smart management in daily societal operations. IEEE-CISIEEE_CISFraud DetectionFraud detection dataset was raised for technique innovation to tackle this problem. For the consideration of the size of the available fraud dataset, this chapter proposes a solution with the combination of the big data techniqueTechniques and the machine learning algorithms. Aside from the raised pipeline of the solution, other identified works include a comparison of four implemented machine learningMachine learningalgorithmsAlgorithm, three surveys into the computing time with respect to the data size, number of executors, and number of cores. Findings from this chapter help finding solutions for more efficient credit fraud detectionFraud detection.

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    Improve the Daily Societal Operations Using Credit Fraud Detection: A Big Data Classification Solution

    Credit fraud detectionCredit fraud detection grows rapidly with the development of electronic payment. It is part of the smart management in daily societal operations. IEEE-CISIEEE_CISFraud DetectionFraud detection dataset was raised for technique innovation to tackle this problem. For the consideration of the size of the available fraud dataset, this chapter proposes a solution with the combination of the big data techniqueTechniques and the machine learning algorithms. Aside from the raised pipeline of the solution, other identified works include a comparison of four implemented machine learningMachine learningalgorithmsAlgorithm, three surveys into the computing time with respect to the data size, number of executors, and number of cores. Findings from this chapter help finding solutions for more efficient credit fraud detectionFraud detection.

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    Improve the Daily Societal Operations Using Credit Fraud Detection: A Big Data Classification Solution

    Credit fraud detectionCredit fraud detection grows rapidly with the development of electronic payment. It is part of the smart management in daily societal operations. IEEE-CISIEEE_CISFraud DetectionFraud detection dataset was raised for technique innovation to tackle this problem. For the consideration of the size of the available fraud dataset, this chapter proposes a solution with the combination of the big data techniqueTechniques and the machine learning algorithms. Aside from the raised pipeline of the solution, other identified works include a comparison of four implemented machine learningMachine learningalgorithmsAlgorithm, three surveys into the computing time with respect to the data size, number of executors, and number of cores. Findings from this chapter help finding solutions for more efficient credit fraud detectionFraud detection.

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    Title:

    Improve the Daily Societal Operations Using Credit Fraud Detection: A Big Data Classification Solution

    Additional title:

    Urban Sustainability

    Contributors:

    Pourroostaei Ardakani, Saeid (author) / Cheshmehzangi, Ali (author)

    Published in:

    Big Data Analytics for Smart Urban Systems ; Chapter: 7 ; 97-110

    Urban Sustainability

    Publication date:

    2023-09-28

    Size:

    14 pages

    ISBN:

    978-981-99-5543-5 , 978-981-99-5542-8

    ISSN:

    2731-6491 , 2731-6483

    DOI:

    https://doi.org/10.1007/978-981-99-5543-5_7

    Type of media:

    Article/Chapter (Book)

    Type of material:

    Electronic Resource

    Language:

    English

    Keywords:

    <italic>Index terms</italic> , Credit fraud detection , Machine learning , Spark MLlib , PCA Environment , Sustainable Development , Statistics, general , Human Geography , Social Sciences

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