SLML
Statistical Learning Models Library: A python library for dynamic surrogates and statistical learning algorithms
Version 2.0.0
License & copyright
© Ahmed H. Bayoumy
How to use SLML package
After installing the SLML package, the functions and classes of SLML module can be imported directly into the python script as follows:
from SLML import *
1 maintainer
Release files for StatLML 2.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| StatLML-2.1.0.tar.gz | 31.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| StatLML-2.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 63.0 kB
Release files / StatLML-2.1.0.tar.gz
| Download URL | StatLML-2.1.0.tar.gz |
|---|---|
| Size | 31.9 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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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.8
|
Release files / StatLML-2.1.0-py3-none-any.whl
| Download URL | StatLML-2.1.0-py3-none-any.whl |
|---|---|
| Size | 31.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a5792e621d3ce79bd373cb0a18a9a84b4e5393c68d383ef8c54aed77f5f225b6
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.8
|
