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k-MEANS CLUSTERING
The next method of analysis involves grouping or clustering data points that share similar attributes using unsupervised learning. An online business, for example, wants to examine a segment of customers that purchase at the same time of the year and discern what factors influence their purchasing behavior. By understanding a given cluster of customers, they can then form decisions regarding which products to recommend to customer groups using promotions and personalized offers. Outside of market research, clustering can also be applied to other scenarios, including pattern recognition, fraud detection, and image processing.
One of the most popular clustering techniques is k-means clustering. As an unsupervised ...
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