Skip to content

Latest commit

 

History

History
25 lines (18 loc) · 987 Bytes

README.md

File metadata and controls

25 lines (18 loc) · 987 Bytes

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.

  1. documentation enhancements:
  • examples how to search the best model over multiple Pipelines using different classifiers
  • added code documentation including docstrings
  1. functionality enhancements:
  • added option to use RandomizedSearchCV
  • the best overall model is provided by train_model()
  • output dataframe is simplified as standard option

Examples

Please refer to HyperclassifierSearch examples.ipynb in the root folder.