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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 31–40 of 46 papers

TitleStatusHype
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
The autofeat Python Library for Automated Feature Engineering and SelectionCode0
IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks—0
Benchmarking Automatic Machine Learning FrameworksCode3
Layered TPOT: Speeding up Tree-based Pipeline OptimizationCode3
AutoLearn - Automated Feature Generation and SelectionCode0
Solving the "false positives" problem in fraud predictionCode0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
One button machine for automating feature engineering in relational databases—0
Learning Feature Engineering for Classification—0
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