Description

• Title:
  Feature Engineering for Anti-Fraud Models Based on Anomaly Detection
• Creator:
  Przekop, Damian
• Description:
  The Central European Journal of Economic Modelling and Econometrics (CEJEME) is a quarterly international journal. It aims to publish articles focusing on mathematical or statistical models in economic sciences. Papers covering the application of existing econometric techniques to a wide variety of problems in economics, in particular in macroeconomics and finance are welcome. Advanced empirical studies devoted to modelling and forecasting of Central and Eastern European economies are of particular interest. Any rigorous methods of statistical inference can be used and articles representing Bayesian econometrics are decidedly within the range of the Journal's interests.;
  Submission Guidelines and Instructions for Authors of accepted papers please visit: http://cejeme.org/submissionguidelines.aspx
• Object availability:
  free access
• Date:
  2020.09.11
• Type:
  Artykuły / Articles
• Source:
  Central European Journal of Economic Modelling and Econometrics; 2020; No 3; 301-316
• Coverage:
  301-316
• Publisher:
  Oddział PAN w Łodzi
• Subject:
  fraud detection;
  application fraud;
  feature engineering;
  anomaly detection;
  risk modeling;
  Nauki Humanistyczne i Społeczne
• Identifier:
  ISSN - 2080-0886, ISSN online - 2080-119X
• Data provider:
  Czasopisma PAN
• Can I use it?:
  seek permission
• Type:
  image