Briefly describe the Iterative K-means clustering algorithm?

Question

06 Mar 2024

Answer :

Word Count : 274

The Iterative K-means clustering algorithm is a popular technique used in machine learning and data analysis for partitioning a dataset into distinct groups or clusters based on similarity patterns. It belongs to the family of unsupervised learning algorithms, where the goal is to identify inherent structures in the data without predefined labels.

The algorithm starts by randomly selecting K initial cluster centroids, where K is the predetermined number _________ __________ ________ __________ ____.
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