Metadata-Version: 1.0
Name: fraud_package
Version: 0.5
Summary: Fraud detection Feature Engineering Pipeline
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
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
        
Platform: UNKNOWN
