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Automated Feature Engineering

7 papers with code ยท Methodology
Subtask of AutoML

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.

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Latest papers without code

Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification

3 Mar 2020

Second, it investigates the performance impact of traditional machine learning based Urdu text document classification methodologies by embedding 10 filter-based feature selection algorithms which have been widely used for other languages.

AUTOMATED FEATURE ENGINEERING DOCUMENT CLASSIFICATION FEATURE ENGINEERING FEATURE SELECTION TRANSFER LEARNING

Lifting Interpretability-Performance Trade-off via Automated Feature Engineering

11 Feb 2020

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

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING

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

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.

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING FRAUD DETECTION

Techniques for Automated Machine Learning

21 Jul 2019

Automated machine learning (AutoML) aims to find optimal machine learning solutions automatically given a machine learning problem.

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING

IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks

13 Sep 2018

In this work, we develop a novel furcated neural network architecture that utilizes domain knowledge as high-level design principles of the network.

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING REPRESENTATION LEARNING

Solving the "false positives" problem in fraud prediction

20 Oct 2017

In this paper, we present an automated feature engineering based approach to dramatically reduce false positives in fraud prediction.

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING

Feature Engineering for Predictive Modeling using Reinforcement Learning

21 Sep 2017

It involves the transformation of given feature space, typically using mathematical functions, with the objective of reducing the modeling error for a given target.

AUTOMATED FEATURE ENGINEERING EFFICIENT EXPLORATION FEATURE ENGINEERING

One button machine for automating feature engineering in relational databases

1 Jun 2017

Feature engineering is one of the most important and time consuming tasks in predictive analytics projects.

AUTOMATED FEATURE ENGINEERING FEATURE ENGINEERING