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Journal code(s)
- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
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Vol. 8, Issue 1 (2019)
Enron investigation using logistic regression with LBFGS solver
Author(s):
Meenu Gupta
Meenu Gupta
Abstract:
This research paper explores the application of machine learning techniques in detecting financial fraud using the Enron scandal as a case study. The Enron scandal is one of the biggest financial scandals in history, involving fraudulent accounting practices that allowed Enron to inflate its earnings and deceive investors and regulators. The paper also discusses the development of a web application to visualize the results of the analysis and provide insights to users.
This research paper explores the application of machine learning techniques in detecting financial fraud using the Enron scandal as a case study. The Enron scandal is one of the biggest financial scandals in history, involving fraudulent accounting practices that allowed Enron to inflate its earnings and deceive investors and regulators. The paper also discusses the development of a web application to visualize the results of the analysis and provide insights to users.
Pages: 689-692 | 142 Views 59 Downloads
How to cite this article:
Meenu Gupta. Enron investigation using logistic regression with LBFGS solver. Pharma Innovation 2019;8(1):689-692. DOI: 10.22271/tpi.2019.v8.i1l.25402
Journal code(s)
- E-ISSN Number: 2277-7695
- P-ISSN Number: 2349-8242
- CODEN Code: PIHNBQ
- ZDB-Number: 2663038-2
- IC Journal ID: 7725
Main Menu
Special Issue
Copyright Form
Identifier
The Pharma Innovation Journal
