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This repository contains an implementation of the K-Means clustering algorithm in Python. K-Means is an unsupervised machine learning algorithm that finds clusters in an N-dimensional space. The implementation provided in this repository allows users to apply K-Means to their own data sets and visualize the resulting clusters.

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MichaelFish199/K-Means-Clustering-Implementation

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K-Means-Clustering-Implementation

Implementation of K-means in python

In this repository I impemented unsupervised algorythm called K-Means that finds clusters in N dimensional space.

This repository consits of 4 jpynb files:

  • K-Means_in_1-Dimension.ipynb (almost complete algorythm in 1-dimension)
  • K-means_in_N-Dimensions_1Iteration.ipynb (1 iteration of algorythm in N-dimension)
  • K-means_in_N-Dimension_Function.ipynb (complete algorythm as Function)
  • K-means_in_N-Dimension_Class.ipynb (complete algorythm as Class)

Results

K-Means_in_1-Dimension

K-means_in_N-Dimensions_1Iteration

K-means_in_N-Dimension_Function

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This repository contains an implementation of the K-Means clustering algorithm in Python. K-Means is an unsupervised machine learning algorithm that finds clusters in an N-dimensional space. The implementation provided in this repository allows users to apply K-Means to their own data sets and visualize the resulting clusters.

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