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Introduction

The K-means algorithm

Discussion about the algorithm

Conclusion

Conclusion

The K-means is the most used clustering algorithm, due to its

inherent simplicity, speed, and empirical success.

However, in its basic form, it has limitations such as the

sensitivity to the initial partition, sensitivity to noise, and the

requierement of predeﬁned number of clusters.

Thus, this algorithm needs to be improved in order to remain

as popular.

J.A Hartigan and M.A Wong Algorithm AS 136 : A K-Means Clustering Algorithm