Fraud detection Feature Engineering Pipeline
Project description
# fraud-package
` A simple feature engineering pipeline `
Built 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
# After Feature Engineering:
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
# Installation
You can install this package using
`bash pip install fraud-package `
# 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 model building. So, to get hands-on working on similar projects. I built this package
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