scNym uses the semi-supervised MixMatch framework and domain adversarial training to take advantage of information in both the labeled and unlabeled datasets.
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Release files for scnym 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scnym-0.3.2.tar.gz | 580.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scnym-0.3.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 649.1 kB
Release files / scnym-0.3.2.tar.gz
| Download URL | scnym-0.3.2.tar.gz |
|---|---|
| Size | 580.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.6.7
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Release files / scnym-0.3.2-py2.py3-none-any.whl
| Download URL | scnym-0.3.2-py2.py3-none-any.whl |
|---|---|
| Size | 68.9 kB |
| Tags | Python 2 Python 3 |
|
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/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.6.7
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