Lecture

K-means Clustering: Assignment and Update Steps

In course

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Description

This lecture covers the assignment step in K-means clustering, where the distance from each data point to each center is calculated, and the data point is assigned to the closest center. It also explains the update step, where the position of the center is computed based on the assignment of the points. Additionally, it discusses the minimization of a loss function in K-means clustering, the effect of different distance metrics, and provides practical examples using ML tools.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_r8pahckb

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Ontological neighbourhood

Information engineering

Machine learning: Unsupervised learning

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