K Means, Kernel Trick, Clustering, Unsupervised Clustering, Data Science.
kernel trick. Why do we need higher dimension feature vectors in K-Means? As mentioned, K-Means performs best when clusters are spherical, dense, and linearly separable, like in the image on the right in Figure 13. For non-linearly separable clusters, like in the image on the left in Figure 12, we