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49 s

Reel · 49 s

K-Means explained: I asked Chile's weather for four kinds of day and it found Santiago

In 49 seconds and narrated: without being told the cities, K-Means put 92% of Santiago's days in one group; Lloyd's algorithm assigns and moves centroids; unscaled, humidity accounts for 76% of the separation; inertia shows no elbow and the silhouette stays within sampling noise across k = 3, 5 and 6; and with k = 8, only 18% of random starts end close to the best inertia, against 38% for k-means++. Muted by default: turn the sound on in the controls.

Length
49 s
Published

Machine learningAlgoritmosPythonDatos

This reel sums up K-Means explained: I asked Chile's weather for four kinds of day and it found Santiago, where the method, the tables and what did not work are.

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