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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 21–30 of 46 papers

TitleStatusHype
Feature Selection as a One-Player Game—0
Feature Selection with Distance Correlation—0
Federated Automated Feature Engineering—0
IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks—0
Learned Feature Importance Scores for Automated Feature Engineering—0
Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering—0
Learning Feature Engineering for Classification—0
Machine Learning for Detecting Data Exfiltration: A Review—0
Quantum Reinforcement Learning Trading Agent for Sector Rotation in the Taiwan Stock Market—0
Semantic-Guided RL for Interpretable Feature Engineering—0
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