prototorch_models/README.md

84 lines
2.6 KiB
Markdown
Raw Normal View History

2021-04-21 13:02:55 +00:00
# ProtoTorch Models
2021-04-21 11:13:28 +00:00
2021-05-10 14:47:28 +00:00
[![Build Status](https://travis-ci.org/si-cim/prototorch_models.svg?branch=main)](https://travis-ci.org/si-cim/prototorch_models)
2021-05-10 14:40:08 +00:00
[![PyPI](https://img.shields.io/pypi/v/prototorch_models)](https://pypi.org/project/prototorch_models/)
2021-05-10 14:39:02 +00:00
2021-04-21 11:30:50 +00:00
Pre-packaged prototype-based machine learning models using ProtoTorch and
PyTorch-Lightning.
2021-04-21 13:02:55 +00:00
## Installation
2021-05-11 14:14:23 +00:00
To install this plugin, simply run the following command:
2021-05-07 13:41:53 +00:00
```sh
2021-05-11 14:14:23 +00:00
pip install prototorch_models
2021-04-21 13:02:55 +00:00
```
The plugin should then be available for use in your Python environment as
`prototorch.models`.
2021-05-11 14:14:23 +00:00
*Note: Installing the models plugin should automatically install a suitable
version of * [ProtoTorch](https://github.com/si-cim/prototorch).
2021-04-21 19:34:32 +00:00
## Development setup
It is recommended that you use a virtual environment for development. If you do
not use `conda`, the easiest way to work with virtual environments is by using
[virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/). Once
you've installed it with `pip install virtualenvwrapper`, you can do the
following:
```sh
export WORKON_HOME=~/pyenvs
mkdir -p $WORKON_HOME
2021-05-07 13:41:53 +00:00
source /usr/local/bin/virtualenvwrapper.sh # location may vary
2021-04-21 19:34:32 +00:00
mkvirtualenv pt
2021-05-07 13:41:53 +00:00
```
Once you have a virtual environment setup, you can start install the `models`
plugin with:
```sh
2021-04-21 19:34:32 +00:00
workon pt
git clone git@github.com:si-cim/prototorch_models.git
cd prototorch_models
git checkout dev
pip install -e .[all] # \[all\] if you are using zsh or MacOS
2021-04-21 19:34:32 +00:00
```
To assist in the development process, you may also find it useful to install
`yapf`, `isort` and `autoflake`. You can install them easily with `pip`.
2021-04-21 13:02:55 +00:00
## Available models
2021-05-11 15:22:02 +00:00
- K-Nearest Neighbors (KNN)
2021-05-11 14:14:23 +00:00
- Learning Vector Quantization 1 (LVQ1)
2021-05-07 13:41:53 +00:00
- Generalized Learning Vector Quantization (GLVQ)
2021-05-09 18:55:07 +00:00
- Generalized Relevance Learning Vector Quantization (GRLVQ)
2021-05-07 13:41:53 +00:00
- Generalized Matrix Learning Vector Quantization (GMLVQ)
- Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
2021-05-11 14:14:23 +00:00
- Learning Vector Quantization Multi-Layer Network (LVQMLN)
2021-04-27 12:35:17 +00:00
- Siamese GLVQ
2021-05-07 13:41:53 +00:00
- Neural Gas (NG)
2021-04-23 15:30:23 +00:00
## Work in Progress
2021-04-29 21:37:22 +00:00
2021-05-07 13:41:53 +00:00
- Classification-By-Components Network (CBC)
2021-05-11 14:14:23 +00:00
- Learning Vector Quantization 2.1 (LVQ2.1)
2021-04-23 15:30:23 +00:00
## Planned models
2021-04-29 21:37:22 +00:00
2021-04-27 12:35:17 +00:00
- Local-Matrix GMLVQ
2021-05-07 13:41:53 +00:00
- Generalized Tangent Learning Vector Quantization (GTLVQ)
- Robust Soft Learning Vector Quantization (RSLVQ)
- Probabilistic Learning Vector Quantization (PLVQ)
- Self-Incremental Learning Vector Quantization (SILVQ)
## FAQ
### How do I update the plugin?
If you have already cloned and installed `prototorch` and the
`prototorch_models` plugin with the `-e` flag via `pip`, all you have to do is
navigate to those folders from your terminal and do `git pull` to update.