Unsupervised Learning
k-means-clustering
An unsupervised learning algorithm used for partitioning data into clusters.
Expanded definition
K-means clustering aims to divide a dataset into K distinct clusters based on feature similarities. The algorithm iteratively assigns data points to the nearest cluster centroid and updates the centroid until convergence. This method is widely used for exploratory data analysis and pattern recognition.
Related terms
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