Credit card fraud problem is one of the soared issues in present. A huge economical damage has severely impacted the cusses who are using and connected with the credit card and to tackle it down, one of the most powerful fraud detection technique is the Machine Learning, and for study or research work a vital number of historical data is present by which this article examines various machine learning fraud detection techniques and compares them using performance measures such as accuracy and precision. This planned system also increases the accuracy of credit card fraud detection. Furthermore, the proposed system uses a learning classification algorithm to classify the data and will pop-up the technique that which will be great for detecting the frauds among the global and anthropoids can save loss of millions of dollars due to established system.


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    Titel :

    Credit Card Fraud Detection Using Local Outlier Factor & Isolation Forest Algorithms: A Complete Analysis


    Beteiligte:


    Erscheinungsdatum :

    2021-12-02


    Format / Umfang :

    1182764 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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