Hurdle
This package contains an implementation of Hurdle Regression, based in part on Geoff Ruddocks implementation and Håvard Hegres 2022 adaption of his implementation.
Usage
from hurdle import HurdleEstimator
from sklearn import linear_model
est = HurdleEstimator(linear_model.LogisticRegression(), linear_model.LinearModel())
est.fit(...)
Metadata
Release files for hurdle 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hurdle-2.0.0.tar.gz | 3.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hurdle-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.4 kB
Release files / hurdle-2.0.0.tar.gz
| Download URL | hurdle-2.0.0.tar.gz |
|---|---|
| Size | 3.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/21.8.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
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Release files / hurdle-2.0.0-py3-none-any.whl
| Download URL | hurdle-2.0.0-py3-none-any.whl |
|---|---|
| Size | 4.0 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/21.8.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
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