Add "K-means clustering description" (#24684)
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Randell Dawson
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Clustering: Is used for exploratory data analysis to find hidden patterns or grouping in data. Take a collection of 1,000,000 different genes, and find a way to automatically group these genes into groups that are somehow similar or related by different variables, such as lifespan, location, roles, and so on.
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K-Means Clustering: The goal of the algorithm is to cluster the data in k-groups. It iteratively assigns data points to their nearest cluster, while keeping their centroids as small as possible.
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Approaches to unsupervised learning include:
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