Weles

Collection of various pattern recognition methods and experimental tools made by Machine Learning Group of Wrocław University of Science and Technology
Current contents
- classifiers
ExposerClassifierLinearClassifierSSGNB
- ensemble
CluensGeometronGESNURSRandomSubspaceUMCE
- meta
PCASSE
- optimizers
RAO
- statistics
t_test_correctedt_test_13t_test_rel
Metadata
Release files for weles 0.6.4
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 | Actions |
|---|---|---|---|---|
| weles-0.6.4.tar.gz | 19.1 kB | Without provenance | Details for weles-0.6.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| weles-0.6.4-py3-none-any.whl | Python 3 | none | any | Details for weles-0.6.4-py3-none-any.whl |
Total release size: 44.8 kB
Release files / weles-0.6.4.tar.gz
| Download URL | weles-0.6.4.tar.gz |
|---|---|
| Size | 19.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2ee9aff4a478a2f056b9f105a4d70ee15f7267439a976691acc64dc45b79e083
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BLAKE2b-256 checksum How to use checksums |
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No |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3
|
Release files / weles-0.6.4-py3-none-any.whl
| Download URL | weles-0.6.4-py3-none-any.whl |
|---|---|
| Size | 25.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
aac1a8c2a02da3f07678de12a8ed87be6580344b5acb111f09e19e1d0e5fab70
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3
|
Security for weles 0.6.4
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