[data request] Credit Card Fraud Detection

• Name of dataset: Credit Card Fraud Detection
• URL of dataset: https://www.kaggle.com/mlg-ulb/creditcardfraud
• License of dataset: https://opendatacommons.org/licenses/dbcl/1.0/
• Short description of dataset and use case(s):

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, we cannot provide the original features and more background information about the data. 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.

Folks who would also like to see this dataset in tensorflow/datasets, please thumbs-up so the developers can know which requests to prioritize.

And if you'd like to contribute the dataset (thank you!), see our guide to adding a dataset.

Start with docs/add_dataset.md and review the linked Kaggle Credit Card Fraud Detection dataset, including its license and schema. Follow the contribution guide to determine the required TFDS entry points and validation steps; done means the dataset is added and usable in tensorflow/datasets.