Machine Learning Method for Detecting and Analysis of Fraud Phone Calls Datasets

  • et al.
N/ACitations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

While using non-stop advancement of correspondences industry, almost all clients steadily appreciate various interchanges companies. To accomplish persuasive and moderate identification with regard to telecom deceit clients, all of us propose an effective and suitable extortion customer discovery method dependent on customer's Call detail Record (CDR). The suggested strategy contains two segments, specific device learning component and file format discovery element. In the equipment wisdom component, a support Vector machine (SVM) computation dependent on aimed knowledge is actually utilized to team clients making use of outline characteristics. Detail evaluation is similarly completed regarding separating the actual detail associated with networks. Outcomes show that these strategies will help rapidly character the ad calls. The actual investigations display that the technique can achieve high reputation precision regarding 97.56%, which exhibit that the proposed technique has progressively brilliant execution in examination with the best in class draws near.

Cite

CITATION STYLE

APA

Sandhya*, S., Karthikeyan, N., & Sruthi, R. (2020). Machine Learning Method for Detecting and Analysis of Fraud Phone Calls Datasets. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 3806–3810. https://doi.org/10.35940/ijrte.f8751.038620

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free