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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

Title	Date	Tasks	Status	Hype
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning	Dec 23, 2020	Automated Feature EngineeringBIG-bench Machine Learning	CodeCode Available	0
Machine Learning for Detecting Data Exfiltration: A Review	Dec 17, 2020	Automated Feature EngineeringBIG-bench Machine Learning	—Unverified	0
DIFER: Differentiable Automated Feature Engineering	Oct 17, 2020	Automated Feature EngineeringBIG-bench Machine Learning	CodeCode Available	1
Cardea: An Open Automated Machine Learning Framework for Electronic Health Records	Oct 1, 2020	Automated Feature EngineeringAutoML	CodeCode Available	1
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research	Sep 14, 2020	Automated Feature EngineeringFeature Engineering	—Unverified	0
Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification	Mar 3, 2020	Automated Feature EngineeringBIG-bench Machine Learning	—Unverified	0
Lifting Interpretability-Performance Trade-off via Automated Feature Engineering	Feb 11, 2020	Automated Feature EngineeringFeature Engineering	CodeCode Available	0
Statistical and machine learning ensemble modelling to forecast sea surface temperature	Sep 18, 2019	Automated Feature EngineeringBIG-bench Machine Learning	—Unverified	0
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs	Sep 3, 2019	Automated Feature EngineeringFeature Engineering	CodeCode Available	0
Techniques for Automated Machine Learning	Jul 21, 2019	Automated Feature EngineeringAutoML	—Unverified	0

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