Metadata-Version: 2.1
Name: kowalsky
Version: 0.0.5
Summary: A small package for all useful ML things
Home-page: https://github.com/NikitaGordia/Kowalsky
Author: Nikita Gordia
Author-email: nikita.gordia@gmail.com
License: UNKNOWN
Description: # Kowalsky, analysis!
        
        A simple package for handful ML things and more.
        
        What's inside?
        
        1. ```analysis``` - method for evaluation of specified model with
           given dataframe. With ```export_test_set=False``` it exports
           ready for submission predictions.
           
        2. df - working with dataframe:
            * ```corr``` - sort all correlated features.
            * ```handle_outliers``` - fill or drop columns with outliers.
            * ```log_transform``` - transform columns with log function.
            * ```group_by_mean``` - make additional columns with aggregated mean
            * ```group_by_max``` - make additional columns with aggregated max
            * ```group_by_min``` - make additional columns with aggregated min
            * ```scale``` - scale columns with Standard of MinMax scalers
            
        3. kag:
            * ```submit``` - make submit-file for kaggle based on sample
            
        4. metrics:
            *  ```rmse``` - RMSE scorer
            *  ```rmsle``` - RMSLE scorer
            
        5. opt - handful methods for working with optuna:
            * ```optimize``` - optimize model with given dataframe
           
        ## Example:
        ```
        !pip install kowalsky --upgrade
        from kowalsky.opt import optimize
        optimize('RFR',
                 path='../input/project/feed.csv',
                 scorer='acc',
                 y_label='y_label',
                 trials=3000)
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
