Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Sarcasm Detection on Reddit Using Classical Machine Learning and Feature Engineering
Sarcasm is common in online discussions, yet difficult for machines to identify because the intended meaning often contradicts the literal wording. In this work, I study sarcasm detection using only classical machine lea…
Feature EngineeringSarcasm DetectionFeature Engineering vs. Deep Learning for Automated Coin Grading: A Comparative Study on Saint-Gaudens Double Eagles
We challenge the common belief that deep learning always trumps older techniques, using the example of grading Saint-Gaudens Double Eagle gold coins automatically. In our work, we put a feature-based Artificial Neural Ne…
Feature EngineeringEdge DetectionClassification of User Satisfaction in HRI with Social Signals in the Wild
Socially interactive agents (SIAs) are being used in various scenarios and are nearing productive deployment. Evaluating user satisfaction with SIAs' performance is a key factor in designing the interaction between the u…
Time Series ClassificationFeature EngineeringOptimizing Stroke Risk Prediction: A Machine Learning Pipeline Combining ROS-Balanced Ensembles and XAI
Stroke is a major cause of death and permanent impairment, making it a major worldwide health concern. For prompt intervention and successful preventative tactics, early risk assessment is essential. To address this chal…
Interpretable Machine LearningFeature EngineeringEnsemble LearningIntegrating Artificial Intelligence and Mixed Integer Linear Programming: Explainable Graph-Based Instance Space Analysis in Air Transportation
This paper analyzes the integration of artificial intelligence (AI) with mixed integer linear programming (MILP) to address complex optimization challenges in air transportation with explainability. The study aims to val…
Dimensionality ReductionFeature EngineeringEnhancing Lung Cancer Treatment Outcome Prediction through Semantic Feature Engineering Using Large Language Models
Accurate prediction of treatment outcomes in lung cancer remains challenging due to the sparsity, heterogeneity, and contextual overload of real-world electronic health data. Traditional models often fail to capture sema…
Feature EngineeringChallenges of Heterogeneity in Big Data: A Comparative Study of Classification in Large-Scale Structured and Unstructured Domains
This study analyzes the impact of heterogeneity ("Variety") in Big Data by comparing classification strategies across structured (Epsilon) and unstructured (Rest-Mex, IMDB) domains. A dual methodology was implemented: ev…
Hyperparameter OptimizationFeature EngineeringML-Tool-Bench: Tool-Augmented Planning for ML Tasks
The development of autonomous machine learning (ML) agents capable of end-to-end data science workflows represents a significant frontier in artificial intelligence. These agents must orchestrate complex sequences of dat…
Hyperparameter OptimizationFeature EngineeringCode GenerationLUMOS: Large User MOdels for User Behavior Prediction
User behavior prediction at scale remains a critical challenge for online B2C platforms. Traditional approaches rely heavily on task-specific models and domain-specific feature engineering. This is time-consuming, comput…
Binary ClassificationFeature EngineeringPULSE-ICU: A Pretrained Unified Long-Sequence Encoder for Multi-task Prediction in Intensive Care Units
Intensive care unit (ICU) data are highly irregular, heterogeneous, and temporally fragmented, posing challenges for generalizable clinical prediction. We present PULSE-ICU, a self-supervised foundation model that learns…
Feature EngineeringTinyViT: Field Deployable Transformer Pipeline for Solar Panel Surface Fault and Severity Screening
Sustained operation of solar photovoltaic assets hinges on accurate detection and prioritization of surface faults across vast, geographically distributed modules. While multi modal imaging strategies are popular, they i…
Feature EngineeringTraining-Free Active Learning Framework in Materials Science with Large Language Models
Active learning (AL) accelerates scientific discovery by prioritizing the most informative experiments, but traditional machine learning (ML) models used in AL suffer from cold-start limitations and domain-specific featu…
Feature EngineeringActive LearningOmniTFT: Omni Target Forecasting for Vital Signs and Laboratory Result Trajectories in Multi Center ICU Data
Accurate multivariate time-series prediction of vital signs and laboratory results is crucial for early intervention and precision medicine in intensive care units (ICUs). However, vital signs are often noisy and exhibit…
Feature EngineeringLess Is More: An Explainable AI Framework for Lightweight Malaria Classification
Background and Objective: Deep learning models have high computational needs and lack interpretability but are often the first choice for medical image classification tasks. This study addresses whether complex neural ne…
Medical Image ClassificationBinary ClassificationFeature EngineeringQuality analysis and evaluation prediction of RAG retrieval based on machine learning algorithms
With the rapid evolution of large language models, retrieval enhanced generation technology has been widely used due to its ability to integrate external knowledge to improve output accuracy. However, the performance of …
Semantic SimilarityFeature EngineeringKnowledge-Informed Automatic Feature Extraction via Collaborative Large Language Model Agents
The performance of machine learning models on tabular data is critically dependent on high-quality feature engineering. While Large Language Models (LLMs) have shown promise in automating feature extraction (AutoFE), exi…
Feature EngineeringBrainRotViT: Transformer-ResNet Hybrid for Explainable Modeling of Brain Aging from 3D sMRI
Accurate brain age estimation from structural MRI is a valuable biomarker for studying aging and neurodegeneration. Traditional regression and CNN-based methods face limitations such as manual feature engineering, limite…
Feature EngineeringAge EstimationSmall Language Models for Phishing Website Detection: Cost, Performance, and Privacy Trade-Offs
Phishing websites pose a major cybersecurity threat, exploiting unsuspecting users and causing significant financial and organisational harm. Traditional machine learning approaches for phishing detection often require e…
Feature EngineeringComparing Task-Agnostic Embedding Models for Tabular Data
Recent foundation models for tabular data achieve strong task-specific performance via in-context learning. Nevertheless, they focus on direct prediction by encapsulating both representation learning and task-specific in…
Representation LearningFeature EngineeringOutlier DetectionAdaptive Dual-Layer Web Application Firewall (ADL-WAF) Leveraging Machine Learning for Enhanced Anomaly and Threat Detection
Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimat…
Feature EngineeringAnomaly Detection