Which mathematical technique is most commonly used in retail machine learning systems to identify distinct customer segments based on purchasing patterns without predefined categories?

Machine learning has revolutionized how retailers analyze customer behavior and optimize operations. Behind these powerful tools are sophisticated mathematical models that transform raw data into actionable insights. This poll tests your knowledge about the mathematical foundations that power retail machine learning applications, which have become essential for competitive advantage in modern retail environments.

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K-means clustering
Linear regression
Naive Bayes classification
Fourier transformation