Low Distortion Local Eigenmaps and its variations.
Project description
pyLDLE2
pyLDLE2 provides an implementation of our manifold learning algorithm LDLE and several variations of it.
Installation
Install pyLDLE2 by running:
python3 -m pip install pyLDLE2
Contribute
- Issue Tracker: github.com/chiggum/pyLDLE2/issues
- Source Code: github.com/chiggum/pyLDLE2
Documentation
https://pyldle2.readthedocs.io/en/latest/
Citation
@article{JMLR:v22:21-0131,
author = {Dhruv Kohli and Alexander Cloninger and Gal Mishne},
title = {LDLE: Low Distortion Local Eigenmaps},
journal = {Journal of Machine Learning Research},
year = {2021},
volume = {22},
number = {282},
pages = {1-64},
url = {http://jmlr.org/papers/v22/21-0131.html}
}
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyLDLE2-0.1.0.tar.gz
(44.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
pyLDLE2-0.1.0-py3-none-any.whl
(54.2 kB
view details)
File details
Details for the file pyLDLE2-0.1.0.tar.gz.
File metadata
- Download URL: pyLDLE2-0.1.0.tar.gz
- Upload date:
- Size: 44.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.3 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.11 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4e1ae07e3f22b16aa999ab4695aa8338cccb3c44e197d4304a0db655f2fe7121
|
|
| MD5 |
0577a3ddf76c2c4c1a5ad04f16a27c27
|
|
| BLAKE2b-256 |
e402bb707f68613b13ac1a427daadec478b7726814c48ad4c145c79f607b80bc
|
File details
Details for the file pyLDLE2-0.1.0-py3-none-any.whl.
File metadata
- Download URL: pyLDLE2-0.1.0-py3-none-any.whl
- Upload date:
- Size: 54.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.3 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.11 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1f441ab0787ec17ce10f0088f28e9f62d80f44f60938ae2c71280bd4f39e02c7
|
|
| MD5 |
bd7fd7c76bbc77f27404072120807d61
|
|
| BLAKE2b-256 |
4c176ae24c45f1b0232d85fbc52fc576400302d829e95cd695fa57e1b266f6e7
|
