Statistical Methods for Data Science
Initialization refers to the process of setting the initial values for the variables or parameters used in a model or algorithm. In the context of clustering, particularly K-means, initialization is crucial because it can significantly affect the convergence of the algorithm and the quality of the resulting clusters. Properly initializing the cluster centroids helps in achieving better results, as poor choices can lead to suboptimal solutions or longer convergence times.
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