Dataset

This dataset was created by Akshat Shah

Contents

Data

We provide you with a data set in CSV format. The data set contains 2 lakhh+ record train instances and 56 thousand test instance There are 31 input features, labeled V1 to V28 and Amount .

The target variable is labeled Class.

Task - Create a Classification model to predict the target variable Class.

1. List of any assumptions that you made
2. Description of your methodology and solution path
3. List of algorithms and techniques you used
4. List of tools and frameworks you used
5. Results and evaluation of your models

How to evaluate the model 1. Use the F1 Score for metrics 2. Any other evaluation measure that you believe is appropriate other than Accuracy.

Dataset

This dataset was created by R. Joseph Manoj, PhD

Contents

In 2019, around 77.5 percent of internet users in Thailand were familiar with the use of credit card numbers and CVV authentication for online payments. CVV stands for card verification value which is used for verifying that the customer has a physical credit or debit card.

Dataset

This dataset was created by Fazela Amjad

Contents

CSV file detailing all individual transactions made by Surrey County Council using purchase cards (corporate credit card) during the period Jan-Mar 2015 (quarter 4). Purchase cards are used mainly by frontline services to support the work we do for residents. See Metadata tab for more details.

CSV file detailing all individual transactions made by Surrey County Council using purchase cards (corporate credit card) during the period Jan-Mar 2015 (quarter 4). Purchase cards are used mainly by frontline services to support the work we do for residents. Specific data schema details can be found on the Local Government Association's (LGA) website http://schemas.opendata.esd.org.uk/Spend.

The same information is available to download as 5 star Linked Data.

This data is published as part of Surrey's obligations for transparency, as set out in the Local Government Transparency Code 2014.

N.B. Prior to April 2015 the Procurement Card Transactions dataset will show minor irregularities with the 'Beneficiary' column whereby some records are shown with split beneficiaries and percentage proportions, instead of a beneficiary name (i.e. SAINSBURYS). This happens where payment has been coded to different internal cost codes. This has been corrected in data post March 2015 and reveals just the beneficiary name.

Update frequency: Quarterly

Review date: No later than end of the month after the quarter end

Temporal coverage: Q4 - Jan-Mar

Geographical coverage: pan-Surrey (though no spatial data published)

Data lineage: Data extracted from SAP, processed to remove irrelevant fields, personal data redacted and re-formatted according to LGA data schema (see above link)

Maintainer contact: Payments Team, Orbis Business Services