Lecture
Kernel K-means: Advanced Machine Learning
Description
This lecture covers the Kernel K-means algorithm, which extends the classical K-means clustering to generate non-linear separations of data points. It explains the algorithm steps, advantages, limitations, and the interpretation of the solution using different kernels. The instructor demonstrates how Kernel K-means can create nonlinear boundaries and provides insights into interpreting the solution with polynomial and RBF kernels.
Official source
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