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@ -9,14 +9,13 @@ prototype-based machine learning algorithms.
This is a Python toolbox brewed at the Mittweida University of Applied Sciences
in Germany for bleeding-edge research in Learning Vector Quantization (LVQ)
methods. Although, there are other (perhaps more extensive) LVQ toolboxes
available out there, the focus of ProtoPy is ease-of-use, extensibility and
speed.
and potentially other prototype-based methods. Although, there are
other (perhaps more extensive) LVQ toolboxes available out there, the focus of
ProtoTorch is ease-of-use, extensibility and speed.
Many popular prototype-based Machine Learning (ML) algorithms like K-Nearest
Neighbors (KNN), Generalized Learning Vector Quantization (GLVQ) and Generalized
Matrix Learning Vector Quantization (GMLVQ) including the recent Learning Vector
Quantization Multi-Layer Network (LVQMLN) are implemented using the "nn" API
Matrix Learning Vector Quantization (GMLVQ) are implemented using the "nn" API
provided by PyTorch.
## Installation
@ -26,6 +25,14 @@ ProtoTorch can be installed using `pip`.
pip install prototorch
```
To install the bleeding-edge features and improvements:
```
git clone https://github.com/si-cim/prototorch.git
git checkout dev
cd prototorch
pip install -e .
```
## Usage
ProtoTorch is modular. It is very easy to use the modular pieces provided by