Papers Feature Engineering
“Feature Engineering” 태그가 달린 논문 1,990편 · 필터 해제
Open Banking Foundational Model: Learning Language Representations from Few Financial Transactions
We introduced a multimodal foundational model for financial transactions that integrates both structured attributes and unstructured textual descriptions into a unified representation. By adapting masked language modelin…
Feature EngineeringHow does My Model Fail? Automatic Identification and Interpretation of Physical Plausibility Failure Modes with Matryoshka Transcoders
Although recent generative models are remarkably capable of producing instruction-following and realistic outputs, they remain prone to notable physical plausibility failures. Though critical in applications, these physi…
Representation LearningFeature EngineeringEnhancing Password Security Through a High-Accuracy Scoring Framework Using Random Forests
Password security plays a crucial role in cybersecurity, yet traditional password strength meters, which rely on static rules like character-type requirements, often fail. Such methods are easily bypassed by common passw…
Feature EngineeringFeature ImportanceSocial Media for Mental Health: Data, Methods, and Findings
There is an increasing number of virtual communities and forums available on the web. With social media, people can freely communicate and share their thoughts, ask personal questions, and seek peer-support, especially t…
Feature EngineeringEmoBang: Detecting Emotion From Bengali Texts
Emotion detection from text seeks to identify an individual's emotional or mental state - positive, negative, or neutral - based on linguistic cues. While significant progress has been made for English and other high-res…
Feature EngineeringAdaRec: Adaptive Recommendation with LLMs via Narrative Profiling and Dual-Channel Reasoning
We propose AdaRec, a few-shot in-context learning framework that leverages large language models for an adaptive personalized recommendation. AdaRec introduces narrative profiling, transforming user-item interactions int…
Feature EngineeringPredicting Cognitive Assessment Scores in Older Adults with Cognitive Impairment Using Wearable Sensors
Background and Objectives: This paper focuses on using AI to assess the cognitive function of older adults with mild cognitive impairment or mild dementia using physiological data provided by a wearable device. Cognitive…
Feature EngineeringGlobal Feature Enhancing and Fusion Framework for Strain Gauge Time Series Classification
Strain Gauge Status (SGS) time series recognition is crucial in the field of intelligent manufacturing based on the Internet of Things, as accurate identification helps timely detection of failed mechanical components, a…
Time Series ClassificationFeature EngineeringGoogle-MedGemma Based Abnormality Detection in Musculoskeletal radiographs
This paper proposes a MedGemma-based framework for automatic abnormality detection in musculoskeletal radiographs. Departing from conventional autoencoder and neural network pipelines, the proposed method leverages the M…
Representation LearningBinary ClassificationFeature EngineeringTransfer LearningInterpretable Heart Disease Prediction via a Weighted Ensemble Model: A Large-Scale Study with SHAP and Surrogate Decision Trees
Cardiovascular disease (CVD) remains a critical global health concern, demanding reliable and interpretable predictive models for early risk assessment. This study presents a large-scale analysis using the Heart Disease …
Feature EngineeringAn Open-Access Benchmark of Statistical and Machine-Learning Anomaly Detection Methods for Battery Applications
Battery safety is critical in applications ranging from consumer electronics to electric vehicles and aircraft, where undetected anomalies could trigger safety hazards or costly downtime. In this study, we present OSBAD …
Unsupervised Anomaly DetectionFeature EngineeringSARIMAX-Based Power Outage Prediction During Extreme Weather Events
This study develops a SARIMAX-based prediction system for short-term power outage forecasting during extreme weather events. Using hourly data from Michigan counties with outage counts and comprehensive weather features,…
Feature EngineeringWindow-Based Feature Engineering for Cognitive Workload Detection
Cognitive workload is a topic of increasing interest across various fields such as health, psychology, and defense applications. In this research, we focus on classifying cognitive workload using the COLET dataset, emplo…
Feature EngineeringSERVIMON: AI-Driven Predictive Maintenance and Real-Time Monitoring for Astronomical Observatories
Objective: ServiMon is designed to offer a scalable and intelligent pipeline for data collection and auditing to monitor distributed astronomical systems such as the ASTRI Mini-Array. The system enhances quality control,…
Feature EngineeringAnomaly DetectionSegmentation over Complexity: Evaluating Ensemble and Hybrid Approaches for Anomaly Detection in Industrial Time Series
In this study, we investigate the effectiveness of advanced feature engineering and hybrid model architectures for anomaly detection in a multivariate industrial time series, focusing on a steam turbine system. We evalua…
Feature EngineeringAnomaly DetectionScalable predictive processing framework for multitask caregiving robots
The rapid aging of societies is intensifying demand for autonomous care robots; however, most existing systems are task-specific and rely on handcrafted preprocessing, limiting their ability to generalize across diverse …
Dimensionality ReductionFeature EngineeringFELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data
Event log data, recording fine-grained user actions and system events, represent one of the most valuable assets for modern digital services. However, the complexity and heterogeneity of industrial event logs--characteri…
Reinforcement LearningFeature EngineeringWavelet-Based Feature Extraction and Unsupervised Clustering for Parity Detection: A Feature Engineering Perspective
This paper explores a deliberately over-engineered approach to the classical problem of parity detection -- determining whether a number is odd or even -- by combining wavelet-based feature extraction with unsupervised c…
Feature EngineeringMLPrE -- A tool for preprocessing and exploratory data analysis prior to machine learning model construction
With the recent growth of Deep Learning for AI, there is a need for tools to meet the demand of data flowing into those models. In some cases, source data may exist in multiple formats, and therefore the source data must…
Feature EngineeringVDSAgents: A PCS-Guided Multi-Agent System for Veridical Data Science Automation
Large language models (LLMs) become increasingly integrated into data science workflows for automated system design. However, these LLM-driven data science systems rely solely on the internal reasoning of LLMs, lacking g…
Feature Engineering