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# kmeans - simple k-means implementation
Simple implementation of the [k-means algortihm](https://en.wikipedia.org/wiki/K-means_clustering).
A visualization for each iteration using matplotlib is created by default.
## Requirements
* recent enough python 3
* (matplotlib and numpy (installable via pipenv))
## Usage
```
usage: kmeans.py [-h] [-n CLUSTERS] [-r RANDOM_POINTS] [-d POINT_DIMENSIONS]
[--dont-visualize] [--max MAX] [--min MIN]
options:
-h, --help show this help message and exit
-n CLUSTERS, --clusters CLUSTERS
-r RANDOM_POINTS, --random-points RANDOM_POINTS
-d POINT_DIMENSIONS, --point-dimensions POINT_DIMENSIONS
--dont-visualize
--max MAX
--min MIN
```
## License
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
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