Answer / Aditi Sharma

Relational evaluation techniques in machine learning compare the performance of different models based on their ability to learn and predict relationships between variables. The components typically include: (1) Relationship Specification, which describes the relationship between variables; (2) Relationship Discovery, which identifies patterns or dependencies between variables; (3) Model Building, which creates a statistical model that captures the discovered relationships; (4) Validation, which assesses the goodness-of-fit and predictive power of the model.

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