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README.md
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@ -8,24 +8,18 @@ PyTorch-Lightning.
## Installation ## Installation
To install this plugin, first install To install this plugin, simply run the following command:
[ProtoTorch](https://github.com/si-cim/prototorch) with:
```sh ```sh
git clone https://github.com/si-cim/prototorch.git && cd prototorch pip install prototorch_models
pip install -e .
```
and then install the plugin itself with:
```sh
git clone https://github.com/si-cim/prototorch_models.git && cd prototorch_models
pip install -e .
``` ```
The plugin should then be available for use in your Python environment as The plugin should then be available for use in your Python environment as
`prototorch.models`. `prototorch.models`.
*Note: Installing the models plugin should automatically install a suitable
version of * [ProtoTorch](https://github.com/si-cim/prototorch).
## Development setup ## Development setup
It is recommended that you use a virtual environment for development. If you do It is recommended that you use a virtual environment for development. If you do
@ -57,17 +51,19 @@ To assist in the development process, you may also find it useful to install
## Available models ## Available models
- Learning Vector Quantization 1 (LVQ1)
- Generalized Learning Vector Quantization (GLVQ) - Generalized Learning Vector Quantization (GLVQ)
- Generalized Relevance Learning Vector Quantization (GRLVQ) - Generalized Relevance Learning Vector Quantization (GRLVQ)
- Generalized Matrix Learning Vector Quantization (GMLVQ) - Generalized Matrix Learning Vector Quantization (GMLVQ)
- Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ) - Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
- Learning Vector Quantization Multi-Layer Network (LVQMLN)
- Siamese GLVQ - Siamese GLVQ
- Neural Gas (NG) - Neural Gas (NG)
## Work in Progress ## Work in Progress
- Classification-By-Components Network (CBC) - Classification-By-Components Network (CBC)
- Learning Vector Quantization Multi-Layer Network (LVQMLN) - Learning Vector Quantization 2.1 (LVQ2.1)
## Planned models ## Planned models
@ -77,7 +73,6 @@ To assist in the development process, you may also find it useful to install
- Probabilistic Learning Vector Quantization (PLVQ) - Probabilistic Learning Vector Quantization (PLVQ)
- Self-Incremental Learning Vector Quantization (SILVQ) - Self-Incremental Learning Vector Quantization (SILVQ)
- K-Nearest Neighbors (KNN) - K-Nearest Neighbors (KNN)
- Learning Vector Quantization 1 (LVQ1)
## FAQ ## FAQ