Simple-Kmeans-Clustering-Algorithm

Abstract

K-means is a centroid-based algorithm, or a distance-based algorithm, where we calculate the distances to assign a point to a cluster. In K-means, each cluster is associated with a centroid. The main objective of the K-Means algorithm is to minimize the sum of distances between the points and their respective cluster centroid. Here is an example of how this algorithm works:

To use this work on your researches or projects you need:

- Python 3.7.0
- Python packages:
- matplotlib
- numpy
- scikit_learn

To install Python:

*First, check if you already have it installed or not*.

```
python3 --version
```

*If you don’t have python 3 in your computer you can use the code below*:

```
sudo apt-get update
sudo apt-get install python3
```

To install packages via pip install:

```
sudo pip3 install matplotlib numpy scikit_learn
```

*If you haven’t installed pip, you can use the codes below in your terminal*:

```
sudo apt-get update
sudo apt install python3-pip
```

*You should check and update your pip*:

```
pip3 install --upgrade pip
```

## GitHub

https://github.com/SamanKhamesian/Simple-Kmeans-Clustering-Algorithm