• Media type: E-Book
  • Title: Comparative Analysis for Fraud Detection Using Logistic Regression, Random Forest and Support Vector Machine
  • Contributor: Kumar, Yogesh [VerfasserIn]; Saini, Sameeka [VerfasserIn]; Payal, Ritu [VerfasserIn]
  • imprint: [S.l.]: SSRN, [2021]
  • Extent: 1 Online-Ressource (6 p)
  • Language: English
  • DOI: 10.2139/ssrn.3751339
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 18, 2020 erstellt
  • Description: For easy payment and classless Credit card payment has become very popular these days. From our bank account we can directly pay the amount online. In spite of this easy payment method it has the disadvantage of having frauds. The unauthorized person accessing the bank details of other person is called as Intruder. These intruders can access some unauthorized transactions also. To prevent this we need some strong mechanisms. In this paper we used three different classification algorithms (Logistic Regression, Random Forest and support vector) for fraud detection and will find out the comparison of accuracy for these three algorithms
  • Access State: Open Access