Which mathematical technique is commonly used in retail machine learning to identify hidden patterns in consumer purchasing behavior without prior labeling?

In today's data-driven retail environment, mathematical models have become essential tools for optimizing operations and predicting consumer behavior. From inventory management to sales forecasting, mathematics provides the foundation for sophisticated retail machine learning algorithms. This trivia question explores a key mathematical concept that revolutionized how retailers approach big data analysis.

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Unsupervised Learning (clustering algorithms like K-means)
Bayesian Inference (conditional probability modeling)
Linear Regression (predictive trend analysis)
Monte Carlo Simulation (randomized probability modeling)