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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 41–46 of 46 papers

TitleStatusHype
FeatGeNN: Improving Model Performance for Tabular Data with Correlation-based Feature Extraction—0
Statistical and machine learning ensemble modelling to forecast sea surface temperature—0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
Feature Selection as a One-Player Game—0
Feature Selection with Distance Correlation—0
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