There are two types of hierarchical clustering – agglomerative and divisive – and they are essentially two sides of the same coin. Agglomerative hierarchical clustering uses a bottom-up approach, working from a single data point and grouping it with the nearest data points in incremental steps until all of the points have been absorbed into a single cluster. Divisive hierarchical clustering works in the opposite way to agglomerative clustering. It begins from the top, where a single cluster encompasses all our data points, and works its way down, splitting the single cluster apart in order of
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