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.
- documentation enhancements:
- examples how to search the best model over multiple Pipelines using different classifiers
- added code documentation including docstrings
- functionality enhancements:
- added option to use RandomizedSearchCV
- the best overall model is provided by train_model()
- output dataframe is simplified as standard option
Examples
1 maintainer
Metadata
1 maintainer
Release files for HyperclassifierSearch 1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| HyperclassifierSearch-1.0.tar.gz | 3.2 kB | Details |
Release files / HyperclassifierSearch-1.0.tar.gz
| Download URL | HyperclassifierSearch-1.0.tar.gz |
|---|---|
| Size | 3.2 kB |
| Tags | Source |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/41.6.0.post20191030 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.5
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