Feature engineering selects, creates, or transforms variables (features) within a dataset to enhance machine learning models' performance and predictive capabilities.
It involves identifying relevant data attributes, combining or generating new features, and optimizing their representation to improve the model's ability to capture patterns and relationships in the data, leading to more accurate and effective predictions or classifications.
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