Lecture

Evaluation for Clustering

In course

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Description

This lecture covers the evaluation of clustering methods, focusing on K-means clustering and the use of evaluation metrics such as RSS, AIC, and BIC to determine the optimal number of clusters. It also discusses the 'elbow' method's limitations and semi-supervised clustering.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_qwy6zt0p

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Ontological neighbourhood

Information engineering

Machine learning: Unsupervised learning

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