Article

Feature Forgetting: A Novel Approach to Redundant Feature Pruning in Automated Feature Engineering

2025-07-16

Abstract excerpt

<title>Abstract</title> <p>The effectiveness of machine learning models heavily depends on the quality and relevance of the features extracted from raw data. Automated Feature Engineering (AutoFE) offers a scalable solution by generating large pools of candidate features. However, the unfiltered expansion of features introduces redundancy, exacerbates computational overhead, and may impair model generalization du...

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Literature Corpus work: 15a23646-880d-5f99-8848-abc126a03af3
DOI: 10.21203/rs.3.rs-7130210/v1

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