Predictive Imputer
Predictive imputation of missing values with sklearn interface. This is a simple implementation of the idea presented in the MissForest R package.
Free software: MIT license
Documentation: https://predictive-imputer.readthedocs.io.
Features
Basic imputation using RandomForestRegressor
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.2.0 (2017-04-01)
Add new models that can be used for imputation: KNN and PCA (@founderfan)
Add early stopping (@founderfan)
0.1.0 (2016-11-28)
First release on PyPI.
1 maintainer
Release files for predictive_imputer 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| predictive_imputer-0.2.0.tar.gz | 12.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| predictive_imputer-0.2.0-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 17.5 kB
Release files / predictive_imputer-0.2.0.tar.gz
| Download URL | predictive_imputer-0.2.0.tar.gz |
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| Size | 12.5 kB |
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Release files / predictive_imputer-0.2.0-py2.py3-none-any.whl
| Download URL | predictive_imputer-0.2.0-py2.py3-none-any.whl |
|---|---|
| Size | 5.0 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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