mlsanityData to 7 Oct 2026

Feature Engineering for Predictive Modeling using Reinforcement Learning

arXiv 1709.07150 ↗First posted 21 Sep 2017cs.AI cs.LG stat.MLcited by 78

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Abstract (arXiv)

Feature engineering is a crucial step in the process of predictive modeling. It involves the transformation of given feature space, typically using mathematical functions, with the objective of reducing the modeling error for a given target. However, there is no well-defined basis for performing effective feature engineering. It involves domain knowledge, intuition, and most of all, a lengthy process of trial and error. The human attention involved in overseeing this process significantly influences the cost of model generation. We present a new framework to automate feature engineering. It is based on performance driven exploration of a transformation graph, which systematically and compactly enumerates the space of given options. A highly efficient exploration strategy is derived through reinforcement learning on past examples.

Key facts. Cited by 78 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Sep 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 13; 2023: 9; 2024: 13; 2025: 25; 2026: 12.

78 papers.

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  1. 2023Data-centric Artificial Intelligence: A Surveycited by 202
  2. 2023Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineeringcited by 125
  3. 2022OpenFE: Automated Feature Generation with Expert-level Performancecited by 52
  4. 2024A Comprehensive Survey on Data Augmentationcited by 38
  5. 2022Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstructioncited by 35
  6. 2025LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizerscited by 35
  7. 2024Evolutionary Large Language Model for Automated Feature Transformationcited by 29
  8. 2024Dynamic and Adaptive Feature Generation with LLMcited by 27
  9. 2022Traceable Automatic Feature Transformation via Cascading Actor-Critic Agentscited by 26
  10. 2021VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decompositioncited by 25
  11. 2023Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspectivecited by 24
  12. 2023Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressionscited by 23
38 more
  1. 2023ChatGPT as your Personal Data Scientistcited by 22
  2. 2024Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuningcited by 21
  3. 2021How Much Automation Does a Data Scientist Want?cited by 20
  4. 2023Out of Context: Investigating the Bias and Fairness Concerns of "Artificial Intelligence as a Service"cited by 15
  5. 2024Automated data processing and feature engineering for deep learning and big data applications: a surveycited by 14
  6. 2024Reinforcement Feature Transformation for Polymer Property Performance Predictioncited by 13
  7. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 12
  8. 2024Topology-aware Reinforcement Feature Space Reconstruction for Graph Datacited by 11
  9. 2025Unsupervised Feature Transformation via In-context Generation, Generator-critic LLM Agents, and Duet-play Teamingcited by 11
  10. 2021FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approachescited by 7
  11. 2023Feature Interaction Aware Automated Data Representation Transformationcited by 6
  12. 2025Autonomous Data Agents: A New Opportunity for Smart Datacited by 6
  13. 2023YOLOv8 for Defect Inspection of Hexagonal Directed Self-Assembly Patterns: A Data-Centric Approachcited by 5
  14. 2024Enhancing Tabular Data Optimization with a Flexible Graph-based Reinforced Exploration Strategycited by 5
  15. 2025FastFT: Accelerating Reinforced Feature Transformation via Advanced Exploration Strategiescited by 5
  16. 2025LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformationcited by 5
  17. 2022Self-Optimizing Feature Transformationcited by 4
  18. 2024IIFE: Interaction Information Based Automated Feature Engineeringcited by 4
  19. 2025Distribution Shift Aware Neural Tabular Learningcited by 4
  20. 2022SapientML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutionscited by 3
  21. 2022The Need for Interpretable Features: Motivation and Taxonomycited by 3
  22. 2022Review of the state of the art in autonomous artificial intelligencecited by 3
  23. 2024Retrieval-Augmented Feature Generation for Domain-Specific Classificationcited by 3
  24. 2025Tabular Feature Discovery With Reasoning Type Explorationcited by 3
  25. 2025ELATE: Evolutionary Language model for Automated Time-series Engineeringcited by 3
  26. 2025DELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogrammingcited by 3
  27. 2026Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learningcited by 3
  28. 2021AEFE: Automatic Embedded Feature Engineering for Categorical Featurescited by 2
  29. 2022A Reinforcement Learning Approach to Domain-Knowledge Inclusion Using Grammar Guided Symbolic Regressioncited by 2
  30. 2022MACFE: A Meta-learning and Causality Based Feature Engineering Frameworkcited by 2
  31. 2022Toward Efficient Automated Feature Engineeringcited by 2
  32. 2025Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformationcited by 2
  33. 2025Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimizationcited by 2
  34. 2025AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessmentcited by 2
  35. 2025FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Datacited by 2
  36. 2026Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Searchcited by 2
  37. 2022An Embedded Feature Selection Framework for Controlcited by 1
  38. 2025Dual-Agent Reinforcement Learning for Automated Feature Generationcited by 1

50 most cited of 78 All 78 (JSON)