Metadata-Version: 2.1
Name: graph-partition
Version: 0.1.1
Summary: Graph partitioning Algorithms
License: MIT
Author: somsubhra88
Requires-Python: >=3.9,<3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: k-means-constrained (==0.7.1)
Requires-Dist: numpy (==1.23.1)
Requires-Dist: scikit-learn (==1.1.1)
Requires-Dist: scipy (>=1.8.1,<2.0.0)
Requires-Dist: torch (==1.12.0)
Description-Content-Type: text/markdown

# Graph Partitioning
Graph Partitioning is an age-old problem with applications in various domains, such as 
routing vehicles for delivery and finding the right target for immunizations to control a 
pandemic. Graph Convolution Networks (GCN) employ deep learning techniques to solve the 
problem of graph partitioning.

# Installation
You can install the graph-partition from PyPI:
```shell
pip install graph-partition
```

# How to Use
Primarily there are three major algorithms are there
- Graph Convolutional Neural Network
- Spectral Clustering
- Constrained K-Means Clustering

### Using of Graph Convolutional Network
```python
import urllib.request
from scipy.spatial import distance_matrix

```
