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This handbook provides a comprehensive overview of set expressions classification, including the basics of set theory, set operations, rule-based classification, and machine learning approaches. It discusses the importance of classifying set expressions in various domains and applications such as mathematics, computer science, and data analysis. The handbook also covers methods for extracting classification rules from labeled datasets and techniques for evaluating and selecting classification rules.

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