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Train multiple classifiers/pipelines

Project 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.

  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

See HyperclassifierSearch on GitHub.

Project details


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This version

1.0

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HyperclassifierSearch-1.0.tar.gz (3.2 kB view hashes)

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