Skip to content

Train several models and evaluate how effectively they predict instances of fraud in bank transactions. Support vector classification, logisitic regression classifier, grid-search optimization

Notifications You must be signed in to change notification settings

sergiopperez/Predict_Fraud

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Predict instances of fraud in bank transactions

Objective: train several models and evaluate how effectively they predict instances of fraud using data based on this dataset from Kaggle.

Each row in fraud_data.csv corresponds to a credit card transaction. Features include confidential variables V1 through V28 as well as Amount which is the amount of the transaction.

The target is stored in the class column, where a value of 1 corresponds to an instance of fraud and 0 corresponds to an instance of not fraud.

About

Train several models and evaluate how effectively they predict instances of fraud in bank transactions. Support vector classification, logisitic regression classifier, grid-search optimization

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published