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Automated Feature Engineering

Automated feature engineering improves upon the traditional approach to feature engineering by automatically extracting useful and meaningful features from a set of related data tables with a framework that can be applied to any problem.

Papers

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Showing 1–10 of 46 papers

TitleStatusHype
Quantum Reinforcement Learning Trading Agent for Sector Rotation in the Taiwan Stock Market—0
LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary OptimizersCode2
Federated Automated Feature Engineering—0
AdaptoML-UX: An Adaptive User-centered GUI-based AutoML Toolkit for Non-AI Experts and HCI ResearchersCode0
Semantic-Guided RL for Interpretable Feature Engineering—0
IIFE: Interaction Information Based Automated Feature EngineeringCode0
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree ReasoningCode1
Learned Feature Importance Scores for Automated Feature Engineering—0
Dynamic and Adaptive Feature Generation with LLM—0
Feature Interaction Aware Automated Data Representation TransformationCode0
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