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 201–250 of 1706 papers

TitleStatusHype
Efficient or Powerful? Trade-offs Between Machine Learning and Deep Learning for Mental Illness Detection on Social Media—0
Integrating convolutional layers and biformer network with forward-forward and backpropagation trainingCode0
Improving Representation Learning of Complex Critical Care Data with ICU-BERT—0
Edge Training and Inference with Analog ReRAM Technology for Hand Gesture Recognition—0
Mitigating Attrition: Data-Driven Approach Using Machine Learning and Data Engineering—0
TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration—0
ML-Driven Approaches to Combat Medicare Fraud: Advances in Class Imbalance Solutions, Feature Engineering, Adaptive Learning, and Business Impact—0
A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems—0
Feature Engineering Approach to Building Load Prediction: A Case Study for Commercial Building Chiller Plant Optimization in Tropical Weather—0
EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models—0
PainDECOG: Machine Learning-Based Identification of Pain Biomarkers from sEEG Signals—0
SEM-CLIP: Precise Few-Shot Learning for Nanoscale Defect Detection in Scanning Electron Microscope Image—0
Recent Advances in Malware Detection: Graph Learning and Explainability—0
Chronic Diseases Prediction Using ML—0
A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective—0
LLM4GNAS: A Large Language Model Based Toolkit for Graph Neural Architecture Search—0
Decision Tree Based Wrappers for Hearing Loss—0
Exploring Patterns Behind Sports—0
Enhancing Physics-Informed Neural Networks Through Feature Engineering—0
Application of quantum machine learning using quantum kernel algorithms on multiclass neuron M type classification—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory—0
From Features to Transformers: Redefining Ranking for Scalable Impact—0
Benchmarking Time Series Forecasting Models: From Statistical Techniques to Foundation Models in Real-World Applications—0
Year-over-Year Developments in Financial Fraud Detection via Deep Learning: A Systematic Literature Review—0
CAAT-EHR: Cross-Attentional Autoregressive Transformer for Multimodal Electronic Health Record EmbeddingsCode0
RAINER: A Robust Ensemble Learning Grid Search-Tuned Framework for Rainfall Patterns Prediction—0
360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation—0
Sample-Efficient Behavior Cloning Using General Domain Knowledge—0
A Transferable Physics-Informed Framework for Battery Degradation Diagnosis, Knee-Onset Detection and Knee Prediction—0
Distributed Multi-Head Learning Systems for Power Consumption Prediction—0
Risk Analysis of Flowlines in the Oil and Gas Sector: A GIS and Machine Learning ApproachCode0
DLinear-based Prediction of Remaining Useful Life of Lithium-Ion Batteries: Feature Engineering through Explainable Artificial Intelligence—0
Algorithmic Derivation of Human Spatial Navigation Indices From Eye Movement Data—0
Challenges and recommendations for Electronic Health Records data extraction and preparation for dynamic prediction modelling in hospitalized patients -- a practical guide—0
Dataset-Agnostic Recommender Systems—0
Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap PredictionCode0
Predicting Vulnerability to Malware Using Machine Learning Models: A Study on Microsoft Windows Machines—0
Multi-Modal Video Feature Extraction for Popularity Prediction—0
Classification of Operational Records in Aviation Using Deep Learning Approaches—0
Dynamic Adaptation in Data Storage: Real-Time Machine Learning for Enhanced Prefetching—0
Assets Forecasting with Feature Engineering and Transformation Methods for LightGBM—0
Three-Class Text Sentiment Analysis Based on LSTM—0
STAHGNet: Modeling Hybrid-grained Heterogenous Dependency Efficiently for Traffic Prediction—0
Intelligent Approaches to Predictive Analytics in Occupational Health and Safety in India—0
Risk-Adjusted Performance of Random Forest Models in High-Frequency Trading—0
PCA-Featured Transformer for Jamming Detection in 5G UAV Networks—0
Hunting Tomorrow's Leaders: Using Machine Learning to Forecast S&P 500 Additions & Removal—0
GLARE: Google Apps Arabic Reviews DatasetCode0
S&P 500 Trend Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified