Metadata-Version: 2.1
Name: pywedge
Version: 0.4.3
Summary: Cleans raw data, runs baseline models
Home-page: https://github.com/taknev83/pywedge/blob/main/pywedge.py
Author: Venkatesh rengarajan Muthu
Author-email: taknev83@gmail.com
License: MIT
Description: # pywedge
        Cleans raw data, runs baseline models. 
        
        Cleans the raw dataframe to fed into ML models. Following data pre_processing based on user preference through dialog box will be carried out,
        1) segregating numeric & categorical columns
        2) missing values imputation for numeric & categorical columns
        3) standardization
        4) feature importance
        5) SMOTE
        6) baseline model
        
        Pre_process_data()
        Inputs: 
        1) train = train dataframe
        2) test = stand out test dataframe (without target column)
        3) c = any redundant column to be removed (like ID column etc., at present supports a single column removal, subsequent version will provision multiple column removal requirements)
        4) y = target column name as a string 
        5) type = Classification / Regression
        
        Returns:
        1) new_X (cleaned feature columns in dataframe)
        2) new_y (cleaned target column in dataframe)  
        3) new_test (cleaned stand out test dataset)
        
        baseline_model()
        - For classification - classification_summary() 
        - For Regression - Regression_summary()
        
        Inputs:
        1) new_x
        2) new_y
        
        Returns:
        Various baseline model metrics 
        
        THIS IS IN BETA VERSION 
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
