MAKING THE K-MEANS ALGORITHM USING THE HAMMING DISTANCE.

In this article I will start in the first part with an introduction to unsupervised learning methods, specifically the K-Means clustering algorithm, the algorithm achieved using the Euclidean distance. In the second part, we modified the K-Means algorithm, which is to say, I realized it with the help of Hamming, and then we compared the clustering time, and we made a parallel between the two algorithms (the K-means algorithm conducted with the Euclidean distance and the algorithm K-Means achieved using the Hamming distance). [ABSTRACT FROM AUTHOR]