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Clustering algorithms group similar data points together from "summary" of Data Science for Business by Foster Provost,Tom Fawcett
Clustering algorithms are a powerful tool in the data scientist's arsenal for uncovering patterns in data. These algorithms are designed to group together data points that share similar characteristics or properties. By doing so, they allow us to identify natural groupings within our data that may not be readily apparent to the naked eye. The process of clustering involves partitioning a set of data points into clusters, with the goal of maximizing the similarity within each cluster while minimizing the similarity between clusters. This is achieved by defining a distance metric that quantifies the similarity between data points, and then using this metric to iteratively assign data points to clusters based on their similarity to one another. One of the key advantages of clustering ...
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