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Feature Engineering

Feature engineering is the process of taking a dataset and constructing explanatory variables — features — that can be used to train a machine learning model for a prediction problem. Often, data is spread across multiple tables and must be gathered into a single table with rows containing the observations and features in the columns.

The traditional approach to feature engineering is to build features one at a time using domain knowledge, a tedious, time-consuming, and error-prone process known as manual feature engineering. The code for manual feature engineering is problem-dependent and must be re-written for each new dataset.

Papers

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Showing 1001–1025 of 1706 papers

TitleStatusHype
Fast Learning and Prediction for Object Detection using Whitened CNN Features—0
Fault Diagnosis of Inter-turn Short Circuit in Permanent Magnet Synchronous Motors with Current Signal Imaging and Unsupervised Learning—0
FeatGeNN: Improving Model Performance for Tabular Data with Correlation-based Feature Extraction—0
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems—0
Feature Cross Search via Submodular Optimization—0
Feature Engineering and Classification Models for Partial Discharge in Power Transformers—0
Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction—0
Feature Engineering Approach to Building Load Prediction: A Case Study for Commercial Building Chiller Plant Optimization in Tropical Weather—0
Feature Engineering-Based Detection of Buffer Overflow Vulnerability in Source Code Using Neural Networks—0
Feature Engineering Combined with 1 D Convolutional Neural Network for Improved Mortality Prediction—0
Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring—0
Feature Engineering for Data-driven Traffic State Forecast in Urban Road Networks—0
Feature Engineering for Knowledge Base Construction—0
Feature Engineering for Map Matching of Low-Sampling-Rate GPS Trajectories in Road Network—0
Feature Engineering for Mid-Price Prediction with Deep Learning—0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
Feature Engineering for Scalable Application-Level Post-Silicon Debugging—0
Feature Engineering for Second Language Acquisition Modeling—0
Feature Engineering for US State Legislative Hearings: Stance, Affiliation, Engagement and Absentees—0
Feature Engineering in Learning-to-Rank for Community Question Answering Task—0
Feature Engineering in the NLI Shared Task 2013: Charles University Submission Report—0
Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions—0
Feature Engineering on LMS Data to Optimize Student Performance Prediction—0
Feature Engineering vs BERT on Twitter Data—0
Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified