Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
SARNet: A Spike-Aware consecutive validation Framework for Accurate Remaining Useful Life Prediction
Accurate prediction of remaining useful life (RUL) is essential to enhance system reliability and reduce maintenance risk. Yet many strong contemporary models are fragile around fault onset and opaque to engineers: short…
Feature EngineeringMachine Learning Enabled Early Warning System For Financial Distress Using Real-Time Digital Signals
The growing instability of both global and domestic economic environments has increased the risk of financial distress at the household level. However, traditional econometric models often rely on delayed and aggregated …
Feature EngineeringSpatio-Temporal Attention Network for Epileptic Seizure Prediction
In this study, we present a deep learning framework that learns complex spatio-temporal correlation structures of EEG signals through a Spatio-Temporal Attention Network (STAN) for accurate predictions of onset of seizur…
Feature EngineeringSeizure predictionIntegrating Transparent Models, LLMs, and Practitioner-in-the-Loop: A Case of Nonprofit Program Evaluation
Public and nonprofit organizations often hesitate to adopt AI tools because most models are opaque even though standard approaches typically analyze aggregate patterns rather than offering actionable, case-level guidance…
Feature EngineeringGeographic Transferability of Machine Learning Models for Short-Term Airport Fog Forecasting
Short-term forecasting of airport fog (visibility < 1.0 km) presents challenges in geographic generalization because many machine learning models rely on location-specific features and fail to transfer across sites. This…
Feature EngineeringHoldout SetCombining ECG Foundation Model and XGBoost to Predict In-Hospital Malignant Ventricular Arrhythmias in AMI Patients
Malignant ventricular arrhythmias (VT/VF) following acute myocardial infarction (AMI) are a major cause of in-hospital death, yet early identification remains a clinical challenge. While traditional risk scores have limi…
Feature EngineeringClinical KnowledgeConditional Diffusion Modeling with Attention for Probabilistic Battery Capacity Prediction under Real-World Condition
Accurate prediction of lithium-ion battery capacity and its associated uncertainty is essential for reliable battery management but remains challenging due to the stochastic nature of aging. This paper presents a new met…
Feature EngineeringNeedles in the Landscape: Semi-Supervised Pseudolabeling for Archaeological Site Discovery under Label Scarcity
Archaeological predictive modelling estimates where undiscovered sites are likely to occur by combining known locations with environmental and geospatial variables, presenting a positive-unlabeled (PU) learning challenge…
Feature EngineeringMTmixAtt: Integrating Mixture-of-Experts with Multi-Mix Attention for Large-Scale Recommendation
Industrial recommender systems critically depend on high-quality ranking models. However, traditional pipelines still rely on manual feature engineering and scenario-specific architectures, which hinder cross-scenario tr…
Feature EngineeringBig Data Approaches to Bovine Bioacoustics: A FAIR-Compliant Dataset and Scalable ML Framework for Precision Livestock Welfare
The convergence of IoT sensing, edge computing, and machine learning is transforming precision livestock farming. Yet bioacoustic data streams remain underused because of computational complexity and ecological validity …
Feature EngineeringVideo AlignmentHybrid Autoencoder-Based Framework for Early Fault Detection in Wind Turbines
Wind turbine reliability is critical to the growing renewable energy sector, where early fault detection significantly reduces downtime and maintenance costs. This paper introduces a novel ensemble-based deep learning fr…
Unsupervised Anomaly DetectionFeature EngineeringConvolutional Attention in Betting Exchange Markets
This study presents the implementation of a short-term forecasting system for price movements in exchange markets, using market depth data and a systematic procedure to enable a fully automated trading system. The case s…
Feature EngineeringA Graph-Attentive LSTM Model for Malicious URL Detection
Malicious URLs pose significant security risks as they facilitate phishing attacks, distribute malware, and empower attackers to deface websites. Blacklist detection methods fail to identify new or obfuscated URLs becaus…
Feature EngineeringUnveiling Gamer Archetypes through Multi modal feature Correlations and Unsupervised Learning
Profiling gamers provides critical insights for adaptive game design, behavioral understanding, and digital well-being. This study proposes an integrated, data-driven framework that combines psychological measures, behav…
Feature EngineeringLLM-Based Data Science Agents: A Survey of Capabilities, Challenges, and Future Directions
Recent advances in large language models (LLMs) have enabled a new class of AI agents that automate multiple stages of the data science workflow by integrating planning, tool use, and multimodal reasoning across text, co…
Multimodal ReasoningFeature EngineeringFairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
Training fair and unbiased machine learning models is crucial for high-stakes applications, yet it presents significant challenges. Effective bias mitigation requires deep expertise in fairness definitions, metrics, data…
Feature EngineeringBrainIB++: Leveraging Graph Neural Networks and Information Bottleneck for Functional Brain Biomarkers in Schizophrenia
The development of diagnostic models is gaining traction in the field of psychiatric disorders. Recently, machine learning classifiers based on resting-state functional magnetic resonance imaging (rs-fMRI) have been deve…
Graph Neural NetworkFeature EngineeringDetecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network
The rise of large language models (LLMs) has enabled the generation of highly persuasive spam reviews that closely mimic human writing. These reviews pose significant challenges for existing detection systems and threate…
Graph Neural NetworkNode ClassificationFeature EngineeringSpam detectionReal-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts
Electroencephalogram (EEG) artifact detection in real-world settings faces significant challenges such as computational inefficiency in multi-channel methods, poor robustness to simultaneous noise, and trade-offs between…
Computational EfficiencyFeature EngineeringArtifact DetectionRegression Language Models for Code
We study code-to-metric regression: predicting numeric outcomes of code executions, a challenging task due to the open-ended nature of programming languages. While prior methods have resorted to heavy and domain-specific…
Feature Engineering