Manhattan distance is a metric used to measure the distance between two points in a grid-based system by only moving along grid lines, resulting in a path that resembles the layout of streets in Manhattan, New York. This distance is calculated as the sum of the absolute differences of their Cartesian coordinates, making it particularly useful for clustering methods that rely on distance metrics to group similar data points.
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