Warning
Repository and Package Name changed to sklearn-lvq!
Generalized Learning Vector Quantization
Scikit-learn compatible implementation of GLVQ, GRLVQ, GMLVQ, LGMLVQ RSLVQ, MRSLVQ and LMRSLVQ.
Compatible with Python2.7, Python3.6 and above.
This implementation is based on the Matlab implementation provided by Biehl, Schneider and Bunte (http://matlabserver.cs.rug.nl/gmlvqweb/web/).
Important Links
- scikit-learn (http://scikit-learn.org/)
- documentation (https://sklearn-lvq.readthedocs.io/en/latest/?badge=latest)
Installation
To install this module run:
pip install .
or
pip install sklearn-lvq
To also install the extras, use
pip install .[docs,examples,tests]
or
pip install -U sklearn-lvq[docs,examples,tests]
Examples
To run the examples:
pip install -U sklearn-lvq[examples]
The examples can be found in the examples directory.
Testing
To run testss:
pip install -U sklearn-lvq[tests]
Tests are located in the sklearn_lvq/tests folder
and can be run with the nosetests command in the main directory.
Documentation
To build the documentation locally, ensure that you have sphinx, sphinx-gallery, pillow, sphinx_rt_theme, metric_learn and matplotlib by executing:
pip install -U sklearn-lvq[docs]
Metadata
Release files for sklearn-lvq 1.1.1
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 | |
|---|---|---|---|---|
| sklearn-lvq-1.1.1.tar.gz | 20.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sklearn_lvq-1.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 58.7 kB
Release files / sklearn-lvq-1.1.1.tar.gz
| Download URL | sklearn-lvq-1.1.1.tar.gz |
|---|---|
| Size | 20.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c62df832a8c59761bd1550e5550e0af2c22f6ed79c164ef668d4c1e97fa05cd4
|
|
BLAKE2b-256 checksum How to use checksums |
0bf7a4785ee044f3e5bb50e14b553dbaff9d0f895ed62e18a581159cfe5be2fb
|
| Upload date | |
|
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/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
|
Release files / sklearn_lvq-1.1.1-py3-none-any.whl
| Download URL | sklearn_lvq-1.1.1-py3-none-any.whl |
|---|---|
| Size | 38.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2c8305cfad6cb0db64c0fdcdebc1e824d2f61c23704c91c0b4f607ae2a3e575f
|
|
BLAKE2b-256 checksum How to use checksums |
4f7c8ecc19d3b45fb1da4eb2926464d05fa2725d675759304744a897e2781a61
|
| Upload date | |
|
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/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
|
Security for sklearn-lvq 1.1.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.