Inertia refers to the tendency of an object to resist changes in its state of motion. In the context of clustering visualization, it can relate to how cluster assignments remain stable or resistant to shifts when the input data is altered, affecting how algorithms like hierarchical and k-means clustering operate. Understanding inertia helps in evaluating the effectiveness of clustering methods by revealing how well-defined and consistent the clusters are when subjected to variations in the dataset.
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