Automated Feature Engineering

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Most implemented papers archive 2025-07-28

23 shown of 23 papers with code (46 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Benchmarking Automatic Machine Learning Frameworks
  17 Aug 2018 4 repositories listed
  AutoML serves as the bridge between varying levels of expertise when designing machine learning systems and expedites the data science process.
• Supervised Video Summarization via Multiple Feature Sets with Parallel Attention
  23 Apr 2021 3 repositories listed
  The proposed architecture utilizes an attention mechanism before fusing motion features and features representing the (static) visual content, i.
• Cardea: An Open Automated Machine Learning Framework for Electronic Health Records
  1 Oct 2020 3 repositories listed
  An estimated 180 papers focusing on deep learning and EHR were published between 2010 and 2018.
• Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
  20 Mar 2016 3 repositories listed
  As the field of data science continues to grow, there will be an ever-increasing demand for tools that make machine learning accessible to non-experts.
• Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
  5 May 2023 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Specifically, we introduce Context-Aware Automated Feature Engineering (CAAFE), a feature engineering method for tabular datasets that utilizes an LLM to iteratively generate additional semantically meaningful features…
• AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
  23 Dec 2020 2 repositories listed
  Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence, stimulated by advances in optimisation techniques and their impact on…
• LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers
  18 Mar 2025 1 repository listed Syntology ran 2 of 11 samples · 9 unverified
  Automated feature engineering plays a critical role in improving predictive model performance for tabular learning tasks.
• AdaptoML-UX: An Adaptive User-centered GUI-based AutoML Toolkit for Non-AI Experts and HCI Researchers
  22 Oct 2024 1 repository listed
  The increasing integration of machine learning across various domains has underscored the necessity for accessible systems that non-experts can utilize effectively.
• IIFE: Interaction Information Based Automated Feature Engineering
  7 Sep 2024 1 repository listed
  Automated feature engineering (AutoFE) is the process of automatically building and selecting new features that help improve downstream predictive performance.
• Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
  12 Jun 2024 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  In tabular prediction tasks, tree-based models combined with automated feature engineering methods often outperform deep learning approaches that rely on learned representations.
• Feature Interaction Aware Automated Data Representation Transformation
  29 Sep 2023 1 repository listed
  Creating an effective representation space is crucial for mitigating the curse of dimensionality, enhancing model generalization, addressing data sparsity, and leveraging classical models more effectively.
• Feature Programming for Multivariate Time Series Prediction
  9 Jun 2023 1 repository listed
  We introduce the concept of programmable feature engineering for time series modeling and propose a feature programming framework.
• Catch: Collaborative Feature Set Search for Automated Feature Engineering
  30 Apr 2023 1 repository listed
  The core to Catch composes a hierarchical-policy reinforcement learning scheme that manifests a collaborative feature engineering exploration and exploitation grounded on the granularity of the whole feature set.
• fseval: A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms
  23 Nov 2022 1 repository listed
  The package is open source and can be installed through PyPI.
• DIFER: Differentiable Automated Feature Engineering
  17 Oct 2020 1 repository listed
  Extensive experiments on classification and regression datasets demonstrate that DIFER can significantly improve the performance of various machine learning algorithms and outperform current state-of-the-art AutoFE…
• Lifting Interpretability-Performance Trade-off via Automated Feature Engineering
  11 Feb 2020 1 repository listed
  Can we train interpretable and accurate models, without timeless feature engineering?
• Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs
  3 Sep 2019 1 repository listed
  Our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to improve the effectiveness of the classification task and allows for an increase in the detection…
• The autofeat Python Library for Automated Feature Engineering and Selection
  22 Jan 2019 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  This paper describes the autofeat Python library, which provides scikit-learn style linear regression and classification models with automated feature engineering and selection capabilities.
• Layered TPOT: Speeding up Tree-based Pipeline Optimization
  18 Jan 2018 1 repository listed
  With the demand for machine learning increasing, so does the demand for tools which make it easier to use.
• AutoLearn - Automated Feature Generation and Selection
  17 Nov 2017 1 repository listed
  In recent years, the importance of feature engineering has been confirmed by the exceptional performance of deep learning techniques, that automate this task for some applications.
• Solving the "false positives" problem in fraud prediction
  20 Oct 2017 1 repository listed
  In this paper, we present an automated feature engineering based approach to dramatically reduce false positives in fraud prediction.
• ExploreKit: Automatic Feature Generation and Selection
  1 Jan 2016 1 repository listed
  To overcome the exponential growth of the feature space, ExploreKit uses a novel machine learning-based feature selection approach to predict the usefulness of new candidate features.
• Deep Feature Synthesis: Towards Automating Data Science Endeavors
  1 Jan 2015 1 repository listed
  In this paper, we develop the Data Science Machine, which is able to derive predictive models from raw data automatically.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.