Semi-Supervised Algorithms
This project has the following algorithms:
- Co-Training
- Tri-Training
- Democratic Co-Learning
- Density Peaks
- STDPNF
Release Notes
See the commit logs at https://github.com/dpr1005/Semisupervised-learning-and-instance-selection-methods.
1 maintainer
Metadata
1 maintainer
Release files for SSL-DNX 2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| SSL-DNX-2.1.tar.gz | 2.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| SSL_DNX-2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.0 kB
Release files / SSL-DNX-2.1.tar.gz
| Download URL | SSL-DNX-2.1.tar.gz |
|---|---|
| Size | 2.6 kB |
| Tags | Source |
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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 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/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12
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Release files / SSL_DNX-2.1-py3-none-any.whl
| Download URL | SSL_DNX-2.1-py3-none-any.whl |
|---|---|
| Size | 3.4 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/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.7.12
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