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Which of the Following Is True About K-means Clustering
Understanding K- Means Clustering Algorithm. This one is NOT TRUE about k-means clustering As k-means is an iterative algorithm it guarantees that it will always converge to the global optimum. K Means Clustring Data Science Data Scientist Data Analyst In other words the K-means algorithm identifies k number of centroids and then allocates every data point to the nearest cluster while keeping the centroids as small as possible. . It is a type of hierarchical clustering. AIt is applicable for data whose variables are categorical. K-Means Clustering is an Unsupervised Learning algorithm which groups the unlabeled dataset into different clusters. K-means clustering is one of the simplest and popular unsupervised machine learning algorithms. Select one or more. This algorithm is an iterative algorithm that partitions the dataset according to their features into K number of predefined non- overlapping distinct clusters or subgr...
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