This is a package for improving the paper that 'Attentional Biased Stochastic Gradient for Imbalanced Classification.' paper
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Metadata
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Release files for absgd 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| absgd-0.0.1.tar.gz | 4.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| absgd-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.9 kB
Release files / absgd-0.0.1.tar.gz
| Download URL | absgd-0.0.1.tar.gz |
|---|---|
| Size | 4.1 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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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.7.7
|
Release files / absgd-0.0.1-py3-none-any.whl
| Download URL | absgd-0.0.1-py3-none-any.whl |
|---|---|
| Size | 5.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1ac8480117c80546ddeea87bb3ffb849655e210d23efe200a57ccafdd90b14c7
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BLAKE2b-256 checksum How to use checksums |
a0696e6aad03731a592f9cefcc25e25db5761ac2be62bd99ffa34a680814d50a
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.7.7
|
Security for absgd 0.0.1
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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