/KMeans-Clustering

Implementing KMeans(++) Clustering models from scratch.

Primary LanguageJupyter Notebook

Introduction

K-means is one of the most widely used unsupervised learning algorithms that solve well-known clustering problems. The procedure follows a simple and easy way to classify a given data set through "k" clusters.

The main idea is to define k centers, one for each cluster. These centers should be placed systematically since different locations causes different results.

Dataset

In this assignment, a custom dataset was generated by using a third-party library.