Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Decision-Focused Learning Enhanced by Automated Feature Engineering for Energy Storage Optimisation
Decision-making under uncertainty in energy management is complicated by unknown parameters hindering optimal strategies, particularly in Battery Energy Storage System (BESS) operations. Predict-Then-Optimise (PTO) appro…
Feature EngineeringKnowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models
Symbolic regression (SR) has emerged as a powerful tool for automated scientific discovery, enabling the derivation of governing equations from experimental data. A growing body of work illustrates the promise of integra…
Feature EngineeringPrompt EngineeringMusic Genre Classification Using Machine Learning Techniques
This paper presents a comparative analysis of machine learning methodologies for automatic music genre classification. We evaluate the performance of classical classifiers, including Support Vector Machines (SVM) and ens…
Genre classificationFeature EngineeringDELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogramming
In real-world applications, domain data often contains identifiable or sensitive attributes, is subject to strict regulations (e.g., HIPAA, GDPR), and requires explicit data feature engineering for interpretability and t…
Reinforcement LearningFeature EngineeringEnd to End Autoencoder MLP Framework for Sepsis Prediction
Sepsis is a life threatening condition that requires timely detection in intensive care settings. Traditional machine learning approaches, including Naive Bayes, Support Vector Machine (SVM), Random Forest, and XGBoost, …
Feature EngineeringAdaptive Physics-Informed Neural Networks with Multi-Category Feature Engineering for Hydrogen Sorption Prediction in Clays, Shales, and Coals
Accurate prediction of hydrogen sorption in clays, shales, and coals is vital for advancing underground hydrogen storage, natural hydrogen exploration, and radioactive waste containment. Traditional experimental methods,…
Hyperparameter OptimizationFeature EngineeringLanguage-Guided Tuning: Enhancing Numeric Optimization with Textual Feedback
Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strategy, feature engineering, and hyperparameters. Traditional approaches tr…
Feature EngineeringELATE: Evolutionary Language model for Automated Time-series Engineering
Time-series prediction involves forecasting future values using machine learning models. Feature engineering, whereby existing features are transformed to make new ones, is critical for enhancing model performance, but i…
Feature EngineeringFeature ImportanceDynamic Design of Machine Learning Pipelines via Metalearning
Automated machine learning (AutoML) has democratized the design of machine learning based systems, by automating model selection, hyperparameter tuning and feature engineering. However, the high computational cost associ…
Feature EngineeringHow Usable is Automated Feature Engineering for Tabular Data?
Tabular data, consisting of rows and columns, is omnipresent across various machine learning applications. Each column represents a feature, and features can be combined or transformed to create new, more informative fea…
Feature EngineeringThe path to a goal: Understanding soccer possessions via path signatures
We present a novel framework for predicting next actions in soccer possessions by leveraging path signatures to encode their complex spatio-temporal structure. Unlike existing approaches, we do not rely on fixed historic…
Feature EngineeringCERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates
Robust generalization under climate change remains a major challenge for machine learning applications in climate science. Most existing approaches struggle to extrapolate beyond the climate they were trained on, leading…
Feature EngineeringConfounding is a Pervasive Problem in Real World Recommender Systems
Unobserved confounding arises when an unmeasured feature influences both the treatment and the outcome, leading to biased causal effect estimates. This issue undermines observational studies in fields like economics, med…
Recommendation SystemsFeature EngineeringLameness detection in dairy cows using pose estimation and bidirectional LSTMs
This study presents a lameness detection approach that combines pose estimation and Bidirectional Long-Short-Term Memory (BLSTM) neural networks. Combining pose-estimation and BLSTMs classifier offers the following advan…
Feature EngineeringPose EstimationFrom Black Box to Transparency: Enhancing Automated Interpreting Assessment with Explainable AI in College Classrooms
Recent advancements in machine learning have spurred growing interests in automated interpreting quality assessment. Nevertheless, existing research suffers from insufficient examination of language use quality, unsatisf…
Feature EngineeringData AugmentationUWB-PostureGuard: A Privacy-Preserving RF Sensing System for Continuous Ergonomic Sitting Posture Monitoring
Improper sitting posture during prolonged computer use has become a significant public health concern. Traditional posture monitoring solutions face substantial barriers, including privacy concerns with camera-based syst…
Feature EngineeringA First Look at Predictability and Explainability of Pre-request Passenger Waiting Time in Ridesharing Systems
Passenger waiting time prediction plays a critical role in enhancing both ridesharing user experience and platform efficiency. While most existing research focuses on post-request waiting time prediction with knowing the…
Feature EngineeringSurformer v1: Transformer-Based Surface Classification Using Tactile and Vision Features
Surface material recognition is a key component in robotic perception and physical interaction, particularly when leveraging both tactile and visual sensory inputs. In this work, we propose Surformer v1, a transformer-ba…
Computational EfficiencyFeature EngineeringAdvanced Hybrid Transformer LSTM Technique with Attention and TS Mixer for Drilling Rate of Penetration Prediction
Rate of Penetration (ROP) prediction is critical for drilling optimization yet remains challenging due to the nonlinear, dynamic, and heterogeneous characteristics of drilling data. Conventional empirical, physics-based,…
Representation LearningFeature EngineeringA Feature Engineering Approach for Business Impact-Oriented Failure Detection in Distributed Instant Payment Systems
Instant payment infrastructures have stringent performance requirements, processing millions of transactions daily with zero-downtime expectations. Traditional monitoring approaches fail to bridge the gap between technic…
Feature EngineeringAnomaly Detection