Metadata-Version: 2.1
Name: scikit-bloom
Version: 0.1.1
Summary: Bloom tricks for text pipelines in scikit-learn.
Home-page: https://koaning.github.io/scikit-bloom/
Author: Vincent D. Warmerdam
License: UNKNOWN
Project-URL: Documentation, https://koaning.github.io/scikit-bloom/
Project-URL: Source Code, https://github.com/koaning/scikit-bloom/
Project-URL: Issue Tracker, https://github.com/koaning/scikit-bloom/issues
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scikit-learn >=1.0.0
Requires-Dist: scikit-partial >=0.1.0
Provides-Extra: dev
Requires-Dist: black >=19.3b0 ; extra == 'dev'
Requires-Dist: flake8-print >=4.0.0 ; extra == 'dev'
Requires-Dist: flake8 >=3.6.0 ; extra == 'dev'
Requires-Dist: interrogate >=1.5.0 ; extra == 'dev'
Requires-Dist: pre-commit >=2.2.0 ; extra == 'dev'
Requires-Dist: pytest >=4.0.2 ; extra == 'dev'
Requires-Dist: scikit-learn >=1.0.0 ; extra == 'dev'
Requires-Dist: scikit-partial >=0.1.0 ; extra == 'dev'

# scikit-bloom

Bloom tricks for text pipelines in scikit-learn. To learn more about this trick, check out [this blogpost](https://explosion.ai/blog/bloom-embeddings).

You can install it via:

```
python -m pip install scikit-bloom
```

And you can import the components via: 

```python
from skbloom import BloomVectorizer, BloomishVectorizer
```

In fairness, while this trick is interesting ... you _might_ be fine just using the `HashingVectorizer` that just comes with sklearn.


