A bank wants to segment its customers into different categories based on their spending habits and transaction history to tailor marketing strategies.
Which machine learning technique is most suitable for this objective?
Clustering
Reinforcement Learning
Regression
Classification
Clustering is the most suitable technique because it involves grouping similar data points together based on features, without using predefined labels. This allows the bank to identify distinct customer segments.
Regression is used for predicting continuous numerical values, which doesn't fit the goal of segmenting customers into categories.
Classification predicts categorical labels based on training data with known categories, but in this case, the categories (customer segments) are not predefined.
Reinforcement Learning involves an agent interacting with an environment to maximize cumulative reward, which is not applicable here.
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