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Fraud detection Feature Engineering Pipeline

Project description

# fraud-package

` A simple feature engineering pipeline `

Built with ❤︎ and :coffee: by [Srikanth Maganti]

Project Specific: https://github.com/srikanthmaganti/Fraud-Detection-Machine-Learning/blob/master/Fraud_Detection_FeatureEngineering_pipeline.ipynb

# Dataset used: ` Take a look at GitHub link `

# Features Before:

  • user_id

  • signup_time

  • purchase_time

  • purchase_value

  • device_id

  • source

  • browser

  • sex

  • age

  • ip_address

  • class

  • country

# Installation

  • You can install this package using

`bash pip install fraud-package `

# After Feature Engineering:

  • Some useful features derived from existing features

  • ratio_fraud_device_id

  • num_trans_device_id

  • ratio_fraud_country

  • num_trans_country

  • ratio_fraud_sex

  • num_trans_sex

  • ratio_fraud_age

  • num_trans_age

  • ratio_fraud_browser

  • num_trans_browser

  • ratio_fraud_source

  • num_trans_source

# Main intention of this Package

Want to implement a feature engineering pipeline because in industry we see few features need to be derived from the existing format of data for better better model building

Project details


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fraud_package-0.4.tar.gz (2.9 kB view hashes)

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