This is a non-IMPACT record, meaning that access to the data is not controlled by IMPACT. For access, see the directions below.

Disclaimer:
This Resource is offered and provided outside of the IMPACT mediation framework. IMPACT and the IMPACT Coordination Council/Blackfire Technology, Inc. expressly disclaim all conditions, representations and warranties including but not limited to Resource availability, quality, accuracy, non-infringement, and non-interference. All Resource information and access is controlled by entities and under terms that are external to the IMPACT legal framework.

Summary

DS-1276
Credit Card Fraud Detection
External Dataset
External Data Source
Kaggle
Unknown
Unknown
56 (lowest rank is 56)

Category & Restrictions

Other
cyber crime
Unrestricted
true

Description


The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset 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.It contains only numerical input variables which are the result of a PCA transformation. Unfortunately, due to confidentiality issues, the original features and more background information about the data are not provided. The dataset has been collected and analysed during a research collaboration of Worldline and the Machine Learning Group of ULB (Universit Libre de Bruxelles) on big data mining and fraud detection.    Features V1, V2, ... V28 are the principal components obtained with PCA, the only features which have not been transformed with PCA are 'Time' and 'Amount'. Feature 'Time' contains the seconds elapsed between each transaction and the first transaction in the dataset. The feature 'Amount' is the transaction Amount, this feature can be used for example-dependant cost-senstive learning. Feature 'Class' is the response variable and it takes value 1 in case of fraud and 0 otherwise.

Additional Details

N/A
false
Unknown
credit, fraud, detection, card, 1276, credit card fraud detection, external, inferlink corporation, corporation, inferlink, external data source, source, transactions, dataset, frauds, datasets, cards, 492, cardholders, 284, european, occurred, september, 2013, days, 807, feature, pca, amount, features, transaction, class, time, learning, transformation, collaboration, variables, worldline, original, account, response, v2, cost, unbalanced, positive, v1, variable, machine, highly, universit, v28, bruxelles, background, input, mining, ulb, analysed, dependant, issues, collected, components, other, takes, libre, transformed, numerical, elapsed, principal, result, 172, senstive, confidentiality, de