Data Science, Machine Learning, Unsupervised Learning.
initial centroids. The k-means algorithm assumes spherical clusters with an equal variance of each cluster. However, in real-world each cluster are different in terms of shape and size which results in sub-optimal results The k-means algorithm requires a pre-defined number of clusters. Choosing the