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An organization wants to group customers into segments based on similarities in their behavior, but they don't have labeled data.
Which machine learning technique should they utilize?
Classification
Time Series Analysis
Clustering
Regression
Clustering - This is the correct answer. Clustering is an unsupervised machine learning technique used to group data into segments based on similarities without requiring labeled data. It is ideal for grouping customers into segments based on their behavior.
Regression is used for predicting continuous numerical values based on input features, not for grouping data or segmenting customers.
Classification is a supervised learning technique where the goal is to categorize data into predefined classes. It requires labeled data, which is not available in this case.
Time Series Analysis is used to analyze data that is collected over time (e.g., stock prices, sales data) to identify trends or patterns. It is not focused on segmenting data into groups based on behavior.
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