Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications
Autoresearch offers a flexible paradigm for automating scientific tasks, in which an AI agent proposes, implements, evaluates, and refines candidate solutions against a quantitative objective. Here, we use composition-ba…
Hyperparameter OptimizationFeature EngineeringOptimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning
In the recent literature, Support Vector Regression (SVR) has been cited as one of the weakest performers on the California Housing benchmark dataset, with Preethi et al. (2025)specifically ranking it last among the algo…
Feature EngineeringFeature ImportanceUserGPT Technical Report
Personalized user understanding from large-scale digital traces remains a fundamental challenge. Traditional user profiling methods rely on discriminative models and manual feature engineering to predict discrete attribu…
Feature EngineeringFlightSense: An End-to-End MLOps Platform for Real-Time Flight Delay Prediction via Rotation-Chain Propagation Features and Agentic Conversational AI
Flight delays impose cascading operational and financial burdens across the aviation network, costing the U.S. economy billions of dollars annually by disrupting interconnected aircraft rotation systems. While prior mach…
Feature EngineeringA Unified Framework for the Detection and Classification of Fatty Pancreas in Ultrasound Images
Non-alcoholic fatty pancreas disease (NAFPD) is an underdiagnosed condition associated with metabolic syndrome, insulin resistance, and increased risk of pancreatic cancer. Diagnosis typically relies on subjective visual…
Feature EngineeringLiver SegmentationTransfer LearningDoes Your Neural Network Extrapolate? Feature Engineering as Identifiability Bias for OOD Generalization
Successful deep neural networks discover salient features of data. We show when and why they fail to learn out-of-distribution (OOD)-relevant representations from an in-distribution (ID) training window. This requires de…
Feature EngineeringHybrid TF--IDF Logistic Regression and MLP Neural Baseline for Indonesian Three-Class Sentiment Analysis on Social Media Text
This paper presents a compact three-class sentiment analysis study for Indonesian social media text. The task is formulated with positive, negative, and neutral outputs derived from a fine-grained emotion dataset. The pr…
Feature EngineeringSentiment AnalysisA Comparative Analysis of Classical Machine Learning and Deep Learning Approaches for Sentiment Classification on IMDb Movie Reviews
This paper presents a comparative study of classical machine learning and deep learning methods for sentiment classification on the IMDb movie reviews dataset. The machine learning pipeline uses TF-IDF features and PyCar…
Feature EngineeringTUANDROMD-X: Advanced Entropy and Visual Analytics Dataset for Enhanced Malware Detection and Classification
Malware and malware-based attacks are becoming more prevalent and complex. Attackers regularly come up with new techniques that have the ability to evade conventional and signature-based malware defense. In order to addr…
Feature EngineeringMalware DetectionPreliminary Insights in Chronos Frequency Data Understanding and Reconstruction
This paper presents a preliminary analysis of the ability of Chronos foundation model to process and internally represent frequency domain information. Foundation models that process time-series data offer practitioners …
Feature EngineeringAutomatic Reflection Level Classification in Hungarian Student Essays
Reflective thinking is a key competency in education, but assessing reflective writing remains a time-consuming and subjective task for education experts. While automated reflective analysis has been explored in several …
Feature EngineeringData AugmentationEvaluating Tabular Representation Learning for Network Intrusion Detection
Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. However, this approach requires domain expertise and runs counter to t…
Unsupervised Anomaly DetectionNetwork Intrusion DetectionRepresentation LearningFeature EngineeringSCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering via Quality-Aware Candidate-Space Reduction
Automatic feature engineering can improve predictive performance on tabular data by generating diverse feature transformations. However, the candidate space induced by combinations of input features and operators grows r…
Feature EngineeringHeterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters
Bayesian finite mixture models can identify discrete risk clusters (low-risk vs. high-risk equipment), but face three critical bottlenecks: (1) insufficient degradation signals from coarse state discretization, (2) unsta…
Computational EfficiencyFeature EngineeringKeyword spotting using convolutional neural network for speech recognition in Hindi
In this study, we investigate the application of keyword spotting (KWS) in the domain of Hindi speech recognition, utilizing a dataset comprising 40,000 audio samples. With a sampling rate of 44 kHz and an average durati…
Computational EfficiencyFeature EngineeringSpeech RecognitionKeyword SpottingMachine Learning and Deep Learning Models for Short Term Electricity Price Forecasting in Australia's National Electricity Market
Short term electricity price forecast is essential in competitive power markets, yet electricity price series exhibit high volatility, irregularity, and non-stationarity. This phenomenon is pronounced in the South Austra…
Feature EngineeringData AugmentationFeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records
Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and structural sparsity inherent to clinical time series. Existing automated me…
Feature EngineeringCoFEE: Reasoning Control for LLM-Based Feature Discovery
Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a target outcome while avoiding leakage, proxies, and post-outcome signal…
Feature EngineeringLearning to count small and clustered objects with application to bacterial colonies
Automated bacterial colony counting from images is an important technique to obtain data required for the development of vaccines and antibiotics. However, bacterial colonies present unique machine vision challenges that…
Feature EngineeringObject CountingLightweight Cybersickness Detection based on User-Specific Eye and Head Tracking Data in Virtual Reality
The occurrence of cybersickness in virtual reality (VR) significantly impairs users' perception and sense of immersion. Therefore, timely detection of cybersickness and the application of appropriate intervention strateg…
Feature EngineeringEnsemble Learning