onelearn: Online learning in Python
Documentation | Reproduce experiments |
onelearn stands for ONE-shot LEARNning. It is a small python package for online learning with Python. It provides :
- online (or one-shot) learning algorithms: each sample is processed once, only a single pass is performed on the data
- including multi-class classification and regression algorithms
- For now, only ensemble methods, namely Random Forests
Installation
The easiest way to install onelearn is using pip
pip install onelearn
But you can also use the latest development from github directly with
pip install git+https://github.com/onelearn/onelearn.git
References
@article{mourtada2019amf,
title={AMF: Aggregated Mondrian Forests for Online Learning},
author={Mourtada, Jaouad and Ga{\"\i}ffas, St{\'e}phane and Scornet, Erwan},
journal={arXiv preprint arXiv:1906.10529},
year={2019}
}
Metadata
Release files for onelearn 0.3.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| onelearn-0.3.0.tar.gz | 11.6 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| onelearn-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.1 MB
Release files / onelearn-0.3.0.tar.gz
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Release files / onelearn-0.3.0-py3-none-any.whl
| Download URL | onelearn-0.3.0-py3-none-any.whl |
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| Size | 11.6 MB |
| Tags | Python 3 |
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