Metadata-Version: 2.1
Name: HyperclassifierSearch
Version: 1.0
Summary: Train multiple classifiers/pipelines
Home-page: https://github.com/dabln/HyperclassifierSearch
Author: Jan Henner
Author-email: mail@janhenner.de
License: UNKNOWN
Description: # HyperclassifierSearch
        
        ## General info
        HyperclassifierSearch allows to train multiple classifiers/pipelines in Python with GridSearchCV or RandomizedSearchCV.
        
        ## Installation
        `pip install HyperclassifierSearch`
        
        ## Requirements
        The code was developed in Python 3. The execution needs Pandas and scikit-learn, i.e. GridSearchCV and RandomizedSearchCV.
        
        ## Enhancements and credits
        The package is build based on code from [David Batista](https://github.com/davidsbatista/machine-learning-notebooks/blob/master/hyperparameter-across-models.ipynb).
        
        1. documentation enhancements:
        - examples how to search the best model over multiple Pipelines using different classifiers
        - added code documentation including docstrings
        
        2. functionality enhancements:
        - added option to use RandomizedSearchCV
        - the best overall model is provided by train_model()
        - output dataframe is simplified as standard option
        
        ## Examples
        See [HyperclassifierSearch on GitHub](https://github.com/dabln/HyperclassifierSearch).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.0
Description-Content-Type: text/markdown
