K Means, Kernel Trick, Clustering, Unsupervised Clustering, Data Science.
where K-Means may result in incorrect clustering. K-Means may not perform well when: Clusters are non-spherical Clusters have different sizes Data has outliers Clusters are non-linearly separable Clusters have overlap Cluster centroids have poor initialization In this article, we will focus on the