Implementations of scikit-learn like ensemble methods in Pytorch
Project description
Implementation of ensemble methods in Pytorch to boost the performance of your model.
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
torchensemble-0.1.1.tar.gz
(19.2 kB
view details)
Built Distribution
File details
Details for the file torchensemble-0.1.1.tar.gz.
File metadata
- Download URL: torchensemble-0.1.1.tar.gz
- Upload date:
- Size: 19.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.23.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 2391f09251eb5217a60ab9e1aa2c4b0705b4800e4939f5061d5857b702d025c4 |
|
| MD5 | b1f73b98a2fb9c960cde4384a48ac300 |
|
| BLAKE2b-256 | 003bc4417d634ba0107dd250a0996150df0ab9fbc1896edeade1873fb6d23cda |
File details
Details for the file torchensemble-0.1.1-py3-none-any.whl.
File metadata
- Download URL: torchensemble-0.1.1-py3-none-any.whl
- Upload date:
- Size: 29.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.23.0 setuptools/50.3.1.post20201107 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | d4f442f161fa96c5e5ac88f3368480ea90ee4a241a3fa589041ed75b4b34baf2 |
|
| MD5 | 93fd1bed92ec5427b1a0c1970592c14c |
|
| BLAKE2b-256 | 1d2a94abb5329a8af251c98eeec213053b8fc3984a36aab1a327c96cc7f75760 |
