SOTAVerified

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 176–200 of 1706 papers

TitleStatusHype
Algorithmic Derivation of Human Spatial Navigation Indices From Eye Movement Data—0
Alejandro Mosquera at SemEval-2021 Task 1: Exploring Sentence and Word Features for Lexical Complexity Prediction—0
A Deep Learning Based Cost Model for Automatic Code Optimization—0
ABM: an automatic supervised feature engineering method for loss based models based on group and fused lasso—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
ALANIS at SemEval-2018 Task 3: A Feature Engineering Approach to Irony Detection in English Tweets—0
A Language-Independent Neural Network for Event Detection—0
A Deep Learning Approach to Mapping Irrigation: IrrMapper-U-Net—0
A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts—0
A Deep Learning Approach to Identify Rock Bolts in Complex 3D Point Clouds of Underground Mines Captured Using Mobile Laser Scanners—0
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods—0
A streamable large-scale clinical EEG dataset for Deep Learning—0
A Deep Learning Approach for Tweet Classification and Rescue Scheduling for Effective Disaster Management—0
AI WALKUP: A Computer-Vision Approach to Quantifying MDS-UPDRS in Parkinson's Disease—0
A Blockchain Transaction Graph based Machine Learning Method for Bitcoin Price Prediction—0
A Progressive Transformer for Unifying Binary Code Embedding and Knowledge Transfer—0
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification—0
A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles—0
Approximation Ratios of Graph Neural Networks for Combinatorial Problems—0
Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model—0
Arabic Named Entity Recognition: What Works and What's Next—0
Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet—0
A Joint Model for Chinese Microblog Sentiment Analysis—0
A Kernel Two-sample Test for Dynamical Systems—0
Approaches to Fraud Detection on Credit Card Transactions Using Artificial Intelligence Methods—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified