Lecture
Clustering Methods: K-means and Density Clustering
Description
This lecture covers the k-means algorithm, introducing the k-means++ algorithm to improve initialization and avoid suboptimal solutions. It explains the kernel trick for non-convex clusters and the application of k-means with kernels. Additionally, it delves into clustering by density, highlighting the DBSCAN algorithm and the evaluation criteria for clustering methods.
Official source
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