Clustering is an ML task that involves grouping similar data points together based on their inherent patterns or similarities. The goal of clustering is to discover the underlying structure in unlabeled data and identify natural groupings or clusters.

Clustering has a wide range of applications, including customer segmentation, image segmentation, document clustering, and market research. It helps in identifying meaningful groups within data, uncovering hidden patterns, and providing insights for decision-making and further analysis.

Clustering application structure

ML.NET doesn’t have a built-in CLI command for clustering. We have to write our own code to accomplish a clustering task. The following playground demonstrates how this can be done. For the convenience of the demonstration, most of the code has been placed into the Program.cs file.

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