crime

Showing 1-1 of 1 results
Credit Card Fraud Detection

Credit Card Fraud Detection

Stefan
Open Dataset
Creators: Worldline and the Machine Learning Group of ULB ((Universite Libre de Bruxelles)
Publication Date: 2016
Creators: Worldline and the Machine Learning Group of ULB ((Universite Libre de Bruxelles)

The Credit Card Fraud Detection dataset is a rich collection of credit card transactions made by European cardholders in September 2013. It presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions. The dataset is 0.15 GB large.

The data has been collected and analysed during a research collaboration of Worldline and the Machine Learning Group (http://mlg.ulb.ac.be) of ULB (Université Libre de Bruxelles) on big data mining and fraud detection.

Each transaction record in the dataset includes several features:​

  • Time: The number of seconds elapsed between this transaction and the first transaction in the dataset.​

  • V1 to V28: These are the result of a Principal Component Analysis (PCA) transformation applied to the original features to protect sensitive information.​

  • Amount: The monetary value of the transaction.​

  • Class: A binary indicator where ‘1’ signifies a fraudulent transaction and ‘0’ denotes a legitimate one.​

Sign In

New to BERD@NFDI? Register

Forgot password?

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.