Machine Learning Ensemble Library
Project description
A library for memory efficient parallelized Ensemble learning
- Documentation available at:
Contact
For questions and comments reach out to sebastianflennerhag@hotmail.com.
This project is hosted at https://github.com/flennerhag/mlens
Project details
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
mlens-0.1.6.tar.gz
(165.0 kB
view details)
Built Distribution
mlens-0.1.6-py2.py3-none-any.whl
(206.4 kB
view details)
File details
Details for the file mlens-0.1.6.tar.gz
.
File metadata
- Download URL: mlens-0.1.6.tar.gz
- Upload date:
- Size: 165.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 78e7dc00937585240b43c99fda7811da1b2413b14e3e6e6060550c5db83561fb |
|
MD5 | 0578cde28f5477ca4393d79cc833d88c |
|
BLAKE2b-256 | 1d7d60a877049bd5f8cc789ccebf00a4282e7346b3f89a2e34a3bf3202d7a230 |
File details
Details for the file mlens-0.1.6-py2.py3-none-any.whl
.
File metadata
- Download URL: mlens-0.1.6-py2.py3-none-any.whl
- Upload date:
- Size: 206.4 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | e6e76ad6addd97f9199c03d7d382e0814d364e80c4541775fdc8a89d7243b3bd |
|
MD5 | d285ae45a3f23c0178f87e9423e111c2 |
|
BLAKE2b-256 | a6225e31cf4c3593efcd49f7203faa333cfd8e9d12b6cb793f339a670d2f43b6 |