Automated Feature Engineering

17 papers with code • 0 benchmarks • 0 datasets

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.

Feature Interaction Aware Automated Data Representation Transformation

ehtesam3154/inhrecon 29 Sep 2023

Creating an effective representation space is crucial for mitigating the curse of dimensionality, enhancing model generalization, addressing data sparsity, and leveraging classical models more effectively.

0
29 Sep 2023

Feature Programming for Multivariate Time Series Prediction

siralex900/featureprogramming 9 Jun 2023

We introduce the concept of programmable feature engineering for time series modeling and propose a feature programming framework.

36
09 Jun 2023

Supervised Video Summarization via Multiple Feature Sets with Parallel Attention

TIBHannover/MSVA 23 Apr 2021

The proposed architecture utilizes an attention mechanism before fusing motion features and features representing the (static) visual content, i. e., derived from an image classification model.

37
23 Apr 2021

AutonoML: Towards an Integrated Framework for Autonomous Machine Learning

uts-caslab/autoweka 23 Dec 2020

Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence, stimulated by advances in optimisation techniques and their impact on selecting ML models/algorithms.

1
23 Dec 2020

DIFER: Differentiable Automated Feature Engineering

pasalab/difer 17 Oct 2020

Extensive experiments on classification and regression datasets demonstrate that DIFER can significantly improve the performance of various machine learning algorithms and outperform current state-of-the-art AutoFE methods in terms of both efficiency and performance.

10
17 Oct 2020

Cardea: An Open Automated Machine Learning Framework for Electronic Health Records

mlbazaar/cardea 1 Oct 2020

An estimated 180 papers focusing on deep learning and EHR were published between 2010 and 2018.

113
01 Oct 2020

Lifting Interpretability-Performance Trade-off via Automated Feature Engineering

agosiewska/SAFE-experiments 11 Feb 2020

Can we train interpretable and accurate models, without timeless feature engineering?

2
11 Feb 2020

Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

Yvan_Lucas/hmm-ccfd 3 Sep 2019

Our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to improve the effectiveness of the classification task and allows for an increase in the detection of fraudulent transactions when combined with the state of the art expert based feature engineering strategy for credit card fraud detection.

0
03 Sep 2019

The autofeat Python Library for Automated Feature Engineering and Selection

cod3licious/autofeat 22 Jan 2019

This paper describes the autofeat Python library, which provides scikit-learn style linear regression and classification models with automated feature engineering and selection capabilities.

470
22 Jan 2019