SMOTE: Synthetic Minority Over-sampling Technique

Abstract

An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of "normal" examples with only a small percentage of "abnormal" or "interesting" examples. It is also the case that the cost of misclassifying an abnormal (interesting) example as a normal example is often much higher than the cost of the reverse error. Under-sampling of the majority (normal) class has been proposed as a good means of increasing the sensitivity of a classifier to the minority class. This paper shows that a combination of our method of over-sampling the minority (abnormal) class and under-sampling the majority (normal) class can achieve better classifier performance (in ROC space) than only under-sampling the majority class. This paper also shows that a combination of our method of over-sampling the minority class and under-sampling the majority class can achieve better classifier performance (in ROC space) than varying the loss ratios in Ripper or class priors in Naive Bayes. Our method of over-sampling the minority class involves creating synthetic minority class examples. Experiments are performed using C4.5, Ripper and a Naive Bayes classifier. The method is evaluated using the area under the Receiver Operating Characteristic curve (AUC) and the ROC convex hull strategy.

References in corpus (1)

• SMOTE: Synthetic Minority Over-sampling Technique

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• Collider signatures of vector-like fermions from a flavor symmetric model
• Heartbeat Anomaly Detection using Adversarial Oversampling
• Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data
• Exploring Content-Based and Meta-Data Analysis for Detecting Fake News Infodemic: A case study on COVID-19
• Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery
• Self-Damaging Contrastive Learning
• Transfer-Learning Oriented Class Imbalance Learning for Cross-Project Defect Prediction
• Machine Learning applied to Multifrequency Data in Astrophysics: Blazar Classification
• A Large-Scale Database for Graph Representation Learning
• Cross-Dataset Design Discussion Mining
• Hyperparameter Optimization for AST Differencing
• Predicting Terrorist Attacks in the United States using Localized News Data
• Treadmill Assisted Gait Spoofing (TAGS): An Emerging Threat to wearable Sensor-based Gait Authentication
• Practical Machine Learning for Cloud Intrusion Detection: Challenges and the Way Forward
• Predicting the Geoeffectiveness of CMEs Using Machine Learning
• Automatic Diagnosis of Pneumothorax from Chest Radiographs: A Systematic Literature Review
• Feature Space Augmentation for Long-Tailed Data
• Graph-Based Machine Learning Improves Just-in-Time Defect Prediction
• Forecasting Cyber Attacks with Imbalanced Data Sets and Different Time Granularities
• Public Reaction to Scientific Research via Twitter Sentiment Prediction
• Using Neural Networks to Differentiate Newly Discovered BL Lacs and FSRQs among the 4FGL Unassociated Sources Employing Gamma-ray, X-ray, UV/Optical and IR Data
• COLA: Cross-city Mobility Transformer for Human Trajectory Simulation
• The First Two Years of FLEET: an Active Search for Superluminous Supernovae
• Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Dataset
• GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
• Hidden Markov Models for Gene Sequence Classification: Classifying the VSG genes in the Trypanosoma brucei Genome
• Exploiting stance hierarchies for cost-sensitive stance detection of Web documents
• Weighted Point Cloud Augmentation for Neural Network Training Data Class-Imbalance
• Class-Weighted Classification: Trade-offs and Robust Approaches
• Annotation Guidelines-Based Knowledge Augmentation: Towards Enhancing Large Language Models for Educational Text Classification
• Root cause prediction based on bug reports
• A Hybrid Intelligent System for Protection of Transmission Lines Connected to PV Farms based on Linear Trends
• Short-term prediction of Electricity Outages Caused by Convective Storms
• Data Leakage and Deceptive Performance: A Critical Examination of Credit Card Fraud Detection Methodologies
• A Time Series Approach To Player Churn and Conversion in Videogames
• Generative Adversarial Networks for Failure Prediction
• Spam filtering on forums: A synthetic oversampling based approach for imbalanced data classification
• Known by the company we keep: `Triadic influence' as a proxy for compatibility in social relationships
• Deep Extrapolation for Attribute-Enhanced Generation
• Using Word Embedding and Convolution Neural Network for Bug Triaging by Considering Design Flaws
• X-ray Sources in the Dwarf Spheroidal Galaxy Draco
• Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions
• Predicting Electricity Infrastructure Induced Wildfire Risk in California
• Classification of blazar candidates of unknown type in Fermi 4LAC by unanimous voting from multiple Machine Learning Algorithms
• Intelligent Protection & Classification of Transients in Two-Core Symmetric Phase Angle Regulating Transformers
• Cybersecurity Misinformation Detection on Social Media: Case Studies on Phishing Reports and Zoom's Threats
• Exploiting Multi-modal Contextual Sensing for City-bus's Stay Location Characterization: Towards Sub-60 Seconds Accurate Arrival Time Prediction
• Optimizing Credit Limit Adjustments Under Adversarial Goals Using Reinforcement Learning
• Modeling PROTAC Degradation Activity with Machine Learning
• Fair-Net: A Network Architecture For Reducing Performance Disparity Between Identifiable Sub-Populations
• VR-FuseNet: A Fusion of Heterogeneous Fundus Data and Explainable Deep Network for Diabetic Retinopathy Classification
• Prediction Model for Mortality Analysis of Pregnant Women Affected With COVID-19
• VOS: a Method for Variational Oversampling of Imbalanced Data
• Periodic Variable Star Classification with Deep Learning: Handling Data Imbalance in an Ensemble Augmentation Way
• AF-DCGAN: Amplitude Feature Deep Convolutional GAN for Fingerprint Construction in Indoor Localization Systems
• Transfer Learning for Thermal Comfort Prediction in Multiple Cities
• Classification of the \emph{Fermi}-LAT Blazar Candidates of Uncertain type using eXtreme Gradient Boosting
• UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks
• A Study on Classification in Imbalanced and Partially-Labelled Data Streams
• A Semi-Supervised Algorithm for Improving the Consistency of Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder Classification
• Class Rectification Hard Mining for Imbalanced Deep Learning
• Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method
• Multi-wavelength study of HESS J1741-302
• Your Face Mirrors Your Deepest Beliefs-Predicting Personality and Morals through Facial Emotion Recognition
• Sampling rate-corrected analysis of irregularly sampled time series
• Learning to Catch Security Patches
• Deep Transfer Learning for Classification of Variable Sources
• Early Identification of Violent Criminal Gang Members
• Adversarial Classifier for Imbalanced Problems
• An Intelligent Decision Support Ensemble Voting Model for Coronary Artery Disease Prediction in Smart Healthcare Monitoring Environments
• Stacking Neural Network Models for Automatic Short Answer Scoring
• Geometric SMOTE: Effective oversampling for imbalanced learning through a geometric extension of SMOTE
• BioMegatron: Larger Biomedical Domain Language Model
• A Deep Probabilistic Model for Customer Lifetime Value Prediction
• To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions
• Is the Stack Distance Between Test Case and Method Correlated With Test Effectiveness?
• Credit card fraud detection using machine learning: A survey
• Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach
• Expansion of Cyber Attack Data From Unbalanced Datasets Using Generative Techniques
• Design of one-year mortality forecast at hospital admission based: a machine learning approach
• Semi-Supervised Classification and Clustering Analysis for Variable Stars
• Learning to Recombine and Resample Data for Compositional Generalization
• Annealing Genetic GAN for Minority Oversampling
• Deep learnig analysis of the inverse seesaw in a 3-3-1 model at the LHC
• Analysis of Vision-based Abnormal Red Blood Cell Classification
• Machine learning-assisted search for novel coagulants: when machine learning can be efficient even if data availability is low
• A Primer on Domain Adaptation
• Misinformation Detection on YouTube Using Video Captions
• Toward Secure Edge Networks Taming Device to Device (D2D) Communication in IoT
• Completeness and Consistency Analysis for Evolving Knowledge Bases
• Feature selection for gesture recognition in Internet-of-Things for healthcare
• Dynamic Experience Replay
• Computational diagnosis and risk evaluation for canine lymphoma
• A Conditional Tabular GAN-Enhanced Intrusion Detection System for Rare Attacks in IoT Networks
• Learning the Relation between Code Features and Code Transforms with Structured Prediction
• Deep Generative Model-based Synthesis of Four-bar Linkage Mechanisms with Target Conditions
• Skew-Probabilistic Neural Networks for Learning from Imbalanced Data
• PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease
• Using Gameplay Videos for Detecting Issues in Video Games
• Driving Safety Prediction and Safe Route Mapping Using In-vehicle and Roadside Data
• The VVV near-IR galaxy catalogue in a Northern part of the Galactic disc
• Learning About Social Context from Smartphone Data: Generalization Across Countries and Daily Life Moments
• In Search of netUnicorn: A Data-Collection Platform to Develop Generalizable ML Models for Network Security Problems
• ${\text{O}}^2$PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection
• An Unbiased Transformer Source Code Learning with Semantic Vulnerability Graph
• Uncertainty Quantification of Wind Gust Predictions in the Northeast United States: An Evidential Neural Network and Explainable Artificial Intelligence Approach
• Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering
• Imbalanced Data Learning by Minority Class Augmentation using Capsule Adversarial Networks
• Hellinger Distance Trees for Imbalanced Streams
• ReMix: Calibrated Resampling for Class Imbalance in Deep learning
• Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning
• Logistic Regression for Massive Data with Rare Events
• Collective Classification of Spam Campaigners on Twitter: A Hierarchical Meta-Path Based Approach
• ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks
• Balanced-MixUp for Highly Imbalanced Medical Image Classification
• Machine learning and natural language processing models to predict the extent of food processing
• CaPC Learning: Confidential and Private Collaborative Learning
• Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification
• Adaptive multi-channel event segmentation and feature extraction for monitoring health outcomes
• HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques
• An Empirical Study on Team Formation in Online Games
• Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
• Are Proactive Interventions for Reddit Communities Feasible?
• Context-driven Active and Incremental Activity Recognition
• Overlapping Word Removal is All You Need: Revisiting Data Imbalance in Hope Speech Detection
• Imbalanced Continual Learning with Partitioning Reservoir Sampling
• A Survey on Curriculum Learning
• Design, Benchmarking and Explainability Analysis of a Game-Theoretic Framework towards Energy Efficiency in Smart Infrastructure
• Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data
• Explainable Software Defect Prediction: Are We There Yet?
• Public Sphere 2.0: Targeted Commenting in Online News Media
• Rationale in Development Chat Messages: An Exploratory Study
• Toward Enhancing Vehicle Color Recognition in Adverse Conditions: A Dataset and Benchmark
• Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-Resolution
• Improving a Credit Scoring Model by Incorporating Bank Statement Derived Features
• STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data
• Predicting Breakdowns in Cloud Services (with SPIKE)
• Predicting Power Electronics Device Reliability under Extreme Conditions with Machine Learning Algorithms
• An Evaluation of Bitcoin Address Classification based on Transaction History Summarization
• AI-based experts' knowledge visualization of cultural heritage: A case study of Terracotta Warriors
• Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection
• Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem
• Enhanced prediction of spine surgery outcomes using advanced machine learning techniques and oversampling methods
• Improving Students Performance in Small-Scale Online Courses -- A Machine Learning-Based Intervention
• AutoLAW: Augmented Legal Reasoning through Legal Precedent Prediction
• Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation
• Multi-objective Asynchronous Successive Halving
• Evaluating the Impact of Data Augmentation on Predictive Model Performance
• Predictive Analytics for Water Asset Management: Machine Learning and Survival Analysis
• Representation Debiasing of Generated Data Involving Domain Experts
• A Visualized Malware Detection Framework with CNN and Conditional GAN
• KPI Extraction from Maintenance Work Orders -- A Comparison of Expert Labeling, Text Classification and AI-Assisted Tagging for Computing Failure Rates of Wind Turbines
• Robust and Effective Malware Detection through Quantitative Data Flow Graph Metrics
• Rotation and flipping invariant self-organizing maps with astronomical images: A cookbook and application to the VLA Sky Survey QuickLook images
• Influence of the Event Rate on Discrimination Abilities of Bankruptcy Prediction Models
• A Novel Resampling Technique for Imbalanced Dataset Optimization
• DIAmante TESS AutoRegressive Planet Search (DTARPS): I. Analysis of 0.9 Million Light Curves
• Sequence embeddings help to identify fraudulent cases in healthcare insurance
• Causal Analysis of Customer Churn Using Deep Learning
• Unsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems
• POISED: Spotting Twitter Spam Off the Beaten Paths
• Surrogate-guided sampling designs for classification of rare outcomes from electronic medical records data
• Classifying blazar candidates from the 3FGL unassociated catalog into BL Lacs and FSRQs using Swift and WISE data
• Detecting broken Absorber Tubes in CSP plants using intelligent sampling and dual loss
• An Ensemble-based Multi-Criteria Decision Making Method for COVID-19 Cough Classification
• Exploiting Data and Human Knowledge for Predicting Wildlife Poaching
• MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation
• A Novel Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using Quantitative Structural MRI in Very Preterm Infants
• CGMOS: Certainty Guided Minority OverSampling
• Automated classification of eclipsing binary systems in the VVV Survey
• Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data
• Oversampling Adversarial Network for Class-Imbalanced Fault Diagnosis
• Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms
• Meta Feature Modulator for Long-tailed Recognition
• Fairness in Forecasting and Learning Linear Dynamical Systems
• A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation
• Compound Batch Normalization for Long-tailed Image Classification
• Study of Constrained Network Structures for WGANs on Numeric Data Generation
• Leveraging Composition-Based Material Descriptors for Machine Learning Optimization
• Reviving Threshold-Moving: a Simple Plug-in Bagging Ensemble for Binary and Multiclass Imbalanced Data
• FraudJudger: Real-World Data Oriented Fraud Detection on Digital Payment Platforms
• Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
• Nearest Labelset Using Double Distances for Multi-label Classification
• Optimizing Cost-Sensitive SVM for Imbalanced Data :Connecting Cluster to Classification
• Investigating the Generalizability of Physiological Characteristics of Anxiety
• Too Trivial To Test? An Inverse View on Defect Prediction to Identify Methods with Low Fault Risk
• A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification
• Decision-forest voting scheme for classification of rare classes in network intrusion detection
• Using a Conditional Generative Adversarial Network to Control the Statistical Characteristics of Generated Images for IACT Data Analysis
• Application of Machine Learning Algorithms in Classifying Postoperative Success in Metabolic Bariatric Surgery: A Comprehensive Study
• Probing intractable beyond-standard-model parameter spaces armed with Machine Learning
• CONAN: Complementary Pattern Augmentation for Rare Disease Detection
• Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model
• Data Mining with Big Data in Intrusion Detection Systems: A Systematic Literature Review
• Neural Network Retraining for Model Serving
• Free energy of (CoxMn1-x)3O4 mixed phases from machine-learning-enhanced ab initio calculations
• Electrocardiogram Classification and Visual Diagnosis of Atrial Fibrillation with DenseECG
• A random shuffle method to expand a narrow dataset and overcome the associated challenges in a clinical study: a heart failure cohort example
• Detection of the most influential variables for preventing postpartum urinary incontinence using machine learning techniques
• Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
• Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric Perspective
• SlimSeiz: Efficient Channel-Adaptive Seizure Prediction Using a Mamba-Enhanced Network
• J-PLUS: Bayesian object classification with a strum of BANNJOS
• A machine learning-based study of open-charm hadrons in proton-proton collisions at the Large Hadron Collider
• Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
• Evaluating the Utility of GAN Generated Synthetic Tabular Data for Class Balancing and Low Resource Settings
• Improving City Life via Legitimate and Participatory Policy-making: A Data-driven Approach in Switzerland
• Counterfeits on Darknet Markets: A measurement between Jan-2014 and Sep-2015
• Attribute Inference Attacks in Online Multiplayer Video Games: a Case Study on Dota2
• PSD2 Explainable AI Model for Credit Scoring
• Loss re-scaling VQA: Revisiting the LanguagePrior Problem from a Class-imbalance View
• Imbalanced Image Classification with Complement Cross Entropy
• Causality-aware counterfactual confounding adjustment for feature representations learned by deep models
• Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders
• Discriminative Ridge Machine: A Classifier for High-Dimensional Data or Imbalanced Data
• Artificial Intelligence for Diabetes Case Management: The Intersection of Physical and Mental Health
• Addressing Class Imbalance in Classification Problems of Noisy Signals by using Fourier Transform Surrogates
• Parallel Grid Pooling for Data Augmentation
• Security Theater: On the Vulnerability of Classifiers to Exploratory Attacks
• Online Variance Reduction for Stochastic Optimization
• Bellwethers: A Baseline Method For Transfer Learning
• Semi-supervised Anomaly Detection on Attributed Graphs
• The Evolution and Future Perspectives of Artificial Intelligence Generated Content
• Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks
• Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation
• A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University
• Artificial Inductive Bias for Synthetic Tabular Data Generation in Data-Scarce Scenarios
• Adaptive Parametric Activation: Unifying and Generalising Activation Functions Across Tasks
• Robustness in Compressed Neural Networks for Object Detection
• Handling Imbalanced Data: A Case Study for Binary Class Problems
• Machine learning approach for mapping the stable orbits around planets
• Friend or Foe? Fake Profile Identification in Online Social Networks
• Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
• Predicting Louisiana Public High School Dropout through Imbalanced Learning Techniques
• Chameleon: Foundation Models for Fairness-aware Multi-modal Data Augmentation to Enhance Coverage of Minorities
• An Integrated Approach for Improving Brand Consistency of Web Content: Modeling, Analysis and Recommendation
• Synthetic Data Generation and Automated Multidimensional Data Labeling for AI/ML in General and Circular Coordinates
• Enhancing Metabolic Syndrome Prediction with Hybrid Data Balancing and Counterfactuals
• An Empirical Study on Code Review Activity Prediction and Its Impact in Practice
• Semi-supervised classification of stars, galaxies and quasars using K-means and random-forest approaches
• Handling Long-Tail Queries with Slice-Aware Conversational Systems
• Offensive Language Analysis using Deep Learning Architecture
• Towards Automatic Bot Detection in Twitter for Health-related Tasks
• Early Identification of Optical Tidal Disruption Events: A science module for the Fink broker
• Construction of Two Statistical Anomaly Features for Small-Sample APT Attack Traffic Classification
• Label-Aware Distribution Calibration for Long-tailed Classification
• Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
• Generalized Data Weighting via Class-level Gradient Manipulation
• Partial Network Alignment with Anchor Meta Path and Truncated Generic Stable Matching
• Machine learning applications for the study of AGN physical properties using photometric observations
• animal2vec and MeerKAT: A self-supervised transformer for rare-event raw audio input and a large-scale reference dataset for bioacoustics
• Exploring the contextual factors affecting multimodal emotion recognition in videos
• SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal
• X-ray Sources Classification Using Machine Learning: A Study with EP-WXT Pathfinder LEIA
• A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning
• Air Pollution Hotspot Detection and Source Feature Analysis using Cross-domain Urban Data
• MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
• Limitations and Alternatives for the Evaluation of Large-scale Link Prediction
• Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning
• Benchmark of Data Preprocessing Methods for Imbalanced Classification
• Automated classification of Chandra X-ray point sources using machine learning methods
• Religious Affiliation in the Twenty-First Century: A Machine Learning Perspective on the World Value Survey
• Fairness in Forecasting of Observations of Linear Dynamical Systems
• Company2Vec -- German Company Embeddings based on Corporate Websites
• Early Life Cycle Software Defect Prediction. Why? How?
• Unique Class Group Based Multi-Label Balancing Optimizer for Action Unit Detection
• An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data
• Interpretable Boosted Decision Tree Analysis for the Majorana Demonstrator
• MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data
• An Empirical Study of the Imbalance Issue in Software Vulnerability Detection
• Repeating versus Nonrepeating Fast Radio Bursts: A Deep Learning Approach to Morphological Characterization
• NEMO: Frequentist Inference Approach to Constrained Linguistic Typology Feature Prediction in SIGTYP 2020 Shared Task
• Towards Competitive Classifiers for Unbalanced Classification Problems: A Study on the Performance Scores
• An Exploratory Approach Towards Investigating and Explaining Vision Transformer and Transfer Learning for Brain Disease Detection
• An explainable hybrid deep learning-enabled intelligent fault detection and diagnosis approach for automotive software systems validation
• Synthetic Tabular Data: Methods, Attacks and Defenses
• Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets
• Buggin: Automatic intrinsic bugs classification model using NLP and ML
• Dynamicasome: a molecular dynamics-guided and AI-driven pathogenicity prediction catalogue for all genetic mutations
• End-to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving
• Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data
• Using Latent Class Analysis to Identify ARDS Sub-phenotypes for Enhanced Machine Learning Predictive Performance
• An Identification of Learners' Confusion through Language and Discourse Analysis
• Attacking Strategies and Temporal Analysis Involving Facebook Discussion Groups
• Exploring Factors Affecting Student Learning Satisfaction during COVID-19 in South Korea
• Predicting Student Performance in Interactive Online Question Pools Using Mouse Interaction Features
• Ensembling classification models based on phalanxes of variables with applications in drug discovery
• Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning
• FedGlu: A personalized federated learning-based glucose forecasting algorithm for improved performance in glycemic excursion regions
• Imbalanced Deep Learning by Minority Class Incremental Rectification
• Textual Membership Queries
• Statically Verifying Continuous Integration Configurations
• A Systematic Study of Online Class Imbalance Learning with Concept Drift
• Reproducible Machine Learning-based Voice Pathology Detection: Introducing the Pitch Difference Feature
• Joint Learning of Domain Classification and Out-of-Domain Detection with Dynamic Class Weighting for Satisficing False Acceptance Rates
• Architectural Selection Framework for Synthetic Network Traffic: Quantifying the Fidelity-Utility Trade-off
• Predicting Workload in Virtual Flight Simulations using EEG Features (Including Post-hoc Analysis in Appendix)
• A Feature Selection Method for High Impedance Fault Detection
• Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier
• Cost-sensitive Multi-class AdaBoost for Understanding Driving Behavior with Telematics
• Score-balanced Loss for Multi-aspect Pronunciation Assessment
• An Adaptive Oversampling Learning Method for Class-Imbalanced Fault Diagnostics and Prognostics
• Playing Minecraft with Behavioural Cloning
• Human and Sheep Facial Landmarks Localisation by Triplet Interpolated Features
• An Online Prediction Approach Based on Incremental Support Vector Machine for Dynamic Multiobjective Optimization
• Predicting Volleyball Season Performance Using Pre-Season Wearable Data and Machine Learning
• MHDeep: Mental Health Disorder Detection System based on Body-Area and Deep Neural Networks
• Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography
• Does Head Label Help for Long-Tailed Multi-Label Text Classification
• Discriminative Sparse Neighbor Approximation for Imbalanced Learning
• An attention model to analyse the risk of agitation and urinary tract infections in people with dementia
• Natural vs Balanced Distribution in Deep Learning on Whole Slide Images for Cancer Detection
• Floods Detection in Twitter Text and Images
• Needmining: Identifying micro blog data containing customer needs
• A Unified Perspective for Loss-Oriented Imbalanced Learning via Localization
• Automatic Time Signature Determination for New Scores Using Lyrics for Latent Rhythmic Structure
• An unsupervised learning approach to evaluate questionnaire data -- what one can learn from violations of measurement invariance
• Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
• LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs
• Meta Learning to Rank for Sparsely Supervised Queries
• FairMask: Better Fairness via Model-based Rebalancing of Protected Attributes
• Deep Learning-Based Transfer Learning for Classification of Cassava Disease
• FALCO: a Foundation model of Astronomical Light Curves for time dOmain astronomy
• Investigate the Essence of Long-Tailed Recognition from a Unified Perspective
• Non-Parametric Stochastic Sequential Assignment With Random Arrival Times
• ClustML: A Measure of Cluster Pattern Complexity in Scatterplots Learnt from Human-labeled Groupings
• Finding and Fixing Spurious Patterns with Explanations
• Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
• Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability
• Landmarks Augmentation with Manifold-Barycentric Oversampling
• Uplink Channel Impulse Response Based Secondary Carrier Prediction
• Handling Class Imbalance Problem in Skin Lesion Classification: Finding Strengths and Weaknesses of Various Balancing Techniques
• BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification
• A Cost-Effective LLM-based Approach to Identify Wildlife Trafficking in Online Marketplaces
• LOD1 3D City Model from LiDAR: The Impact of Segmentation Accuracy on Quality of Urban 3D Modeling and Morphology Extraction
• Downstream-Pretext Domain Knowledge Traceback for Active Learning
• C-RADAR: A Centralized Deep Learning System for Intrusion Detection in Software Defined Networks
• Posterior Re-calibration for Imbalanced Datasets
• A little goes a long way: Improving toxic language classification despite data scarcity
• Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda
• Quantitative predictions of photo-emission dynamics in metal halide perovskites via machine learning
• Astronomical image time series classification using CONVolutional attENTION (ConvEntion)
• Shedding light on underrepresentation and Sampling Bias in machine learning
• Box Drawings for Learning with Imbalanced Data
• Efficacy of Statistical and Artificial Intelligence-based False Information Cyberattack Detection Models for Connected Vehicles
• FRUGAL: Unlocking SSL for Software Analytics
• Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
• Multi-Lead ECG Classification via an Information-Based Attention Convolutional Neural Network
• How to Improve AI Tools (by Adding in SE Knowledge): Experiments with the TimeLIME Defect Reduction Tool
• Towards a Resilient Machine Learning Classifier -- a Case Study of Ransomware Detection
• Assessing the Quality of Web Content
• Sequential Targeting: an incremental learning approach for data imbalance in text classification
• Metric Learning from Imbalanced Data
• Contour Detection in Cassini ISS images based on Hierarchical Extreme Learning Machine and Dense Conditional Random Field
• Orometric Methods in Bounded Metric Data
• Improving Surrogate Model Accuracy for the LCLS-II Injector Frontend Using Convolutional Neural Networks and Transfer Learning
• Improving fraud prediction with incremental data balancing technique for massive data streams
• Precisely Predicting Acute Kidney Injury with Convolutional Neural Network Based on Electronic Health Record Data
• Semi-supervised and Unsupervised Methods for Heart Sounds Classification in Restricted Data Environments
• Smartphone Security Behavioral Scale: A New Psychometric Measurement for Smartphone Security
• Complex Wavelet SSIM based Image Data Augmentation
• Superensemble Classifier for Improving Predictions in Imbalanced Datasets
• Scalable Solutions for Automated Single Pulse Identification and Classification in Radio Astronomy
• Effect of Text Processing Steps on Twitter Sentiment Classification using Word Embedding
• FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
• Cavity Filling: Pseudo-Feature Generation for Multi-Class Imbalanced Data Problems in Deep Learning
• GLA-Net: An Attention Network with Guided Loss for Mismatch Removal
• The survival of start-ups in time of crisis. A machine learning approach to measure innovation
• Conductor Galloping Prediction on Imbalanced Datasets: SVM with Smart Sampling
• Modified SMOTE Using Mutual Information and Different Sorts of Entropies
• Using Decision Tree Learner to Classify Solvency Position for Thai Non-life Insurance Companies
• Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation
• Learned Indexes for Dynamic Workloads
• Rough extreme learning machine: a new classification method based on uncertainty measure
• Training Multi-Speaker Neural Text-to-Speech Systems using Speaker-Imbalanced Speech Corpora
• VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository
• SelectNet: Learning to Sample from the Wild for Imbalanced Data Training
• Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks
• Recruiting from the network: discovering Twitter users who can help combat Zika epidemics
• Non-Sentential Utterances in Dialogue: Experiments in Classification and Interpretation
• Co-supervised learning paradigm with conditional generative adversarial networks for sample-efficient classification
• On convex decision regions in deep network representations
• A Longitudinal Framework for Predicting Nonresponse in Panel Surveys
• Online Anomaly Detection via Class-Imbalance Learning
• Deep Imbalanced Attribute Classification using Visual Attention Aggregation
• Characterizing Fan Behavior to Study Para Social Breakups
• DRAST -- A Deep Learning and AST Based Approach for Bug Localization
• Imbalanced Regression Pipeline Recommendation
• F^2-Softmax: Diversifying Neural Text Generation via Frequency Factorized Softmax
• Consistent Batch Normalization for Weighted Loss in Imbalanced-Data Environment
• Deep Learning Applications Based on WISE Infrared Data: Classification of Stars, Galaxies and Quasars
• Beyond Trial-and-Error: Predicting User Abandonment After a Moderation Intervention
• Data Distribution-based Curriculum Learning
• Natural Language Processing for EHR-Based Computational Phenotyping
• Asymmetric Impurity Functions, Class Weighting, and Optimal Splits for Binary Classification Trees
• Class-Wise Difficulty-Balanced Loss for Solving Class-Imbalance
• Mechanical behavior of high-entropy alloys: A review
• Online Self-Evolving Anomaly Detection in Cloud Computing Environments
• Empirical Similarity for Absent Data Generation in Imbalanced Classification
• Class Augmented Semi-Supervised Learning for Practical Clinical Analytics on Physiological Signals
• An extensive empirical study of inconsistent labels in multi-version-project defect data sets
• DTWSSE: Data Augmentation with a Siamese Encoder for Time Series
• Interpret-able feedback for AutoML systems
• Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks
• One for More: Selecting Generalizable Samples for Generalizable ReID Model
• Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data
• Symmetry constrained neural networks for detection and localization of damage in metal plates
• Credit scoring using neural networks and SURE posterior probability calibration
• Using Natural Language Processing to Screen Patients with Active Heart Failure: An Exploration for Hospital-wide Surveillance
• Synthetic Flight Data Generation Using Generative Models
• Importance Weighted Adversarial Discriminative Transfer for Anomaly Detection
• Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine Learning
• mldr.resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms
• Machine Learning applications for Cataclysmic Variable discovery in the ZTF alert stream
• Defect Reduction Planning (using TimeLIME)
• From Generalized zero-shot learning to long-tail with class descriptors
• Predicting health inspection results from online restaurant reviews
• F-measure Maximizing Logistic Regression
• Multi-stage Neural Networks with Single-sided Classifiers for False Positive Reduction and its Evaluation using Lung X-ray CT Images
• SetConv: A New Approach for Learning from Imbalanced Data
• NodeImport: Imbalanced Node Classification with Node Importance Assessment
• ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data
• Robust COVID-19 Detection from Cough Sounds using Deep Neural Decision Tree and Forest: A Comprehensive Cross-Datasets Evaluation
• Towards automated symptoms assessment in mental health
• AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)
• Semi-supervised learning for medical image classification using imbalanced training data
• Methods for Recovering Conditional Independence Graphs: A Survey
• Building Better Quality Predictors Using "$\epsilon$-Dominance"
• Enhancing Mortality Prediction in Heart Failure Patients: Exploring Preprocessing Methods for Imbalanced Clinical Datasets
• Dealing with the data imbalance problem on pulsar candidates sifting based on feature selection
• Username Squatting on Online Social Networks: A Study on X
• EPARS: Early Prediction of At-risk Students with Online and Offline Learning Behaviors
• Evaluating Binary Outcome Classifiers Estimated from Survey Data
• Song-based Classification techniques for Endangered Bird Conservation
• Code Revert Prediction with Graph Neural Networks: A Case Study at J.P. Morgan Chase
• ACE: Adaptive Confusion Energy for Natural World Data Distribution
• Analysis of skin lesion images with deep learning
• Crime Prediction Using Spatio-Temporal Data
• NeuroLGP-SM: Scalable Surrogate-Assisted Neuroevolution for Deep Neural Networks
• An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data
• PCA-Based Missing Information Imputation for Real-Time Crash Likelihood Prediction Under Imbalanced Data
• Audio-based performance evaluation of squash players
• Tips and Tricks to Improve CNN-based Chest X-ray Diagnosis: A Survey
• Constructing balanced datasets for predicting failure modes in structural systems under seismic hazards
• Multi-Label Sampling based on Local Label Imbalance
• Data Augmentation Imbalance For Imbalanced Attribute Classification
• Synthetic Data Generation for Classifying Electrophysiological and Morpho-Electrophysiological Neurons from Mouse Visual Cortex
• Automatic Stroke Classification of Tabla Accompaniment in Hindustani Vocal Concert Audio
• Teaching a Massive Open Online Course on Natural Language Processing
• Towards Automatic Generation of Short Summaries of Commits
• A Smartphone-Based Method for Assessing Tomato Nutrient Status through Trichome Density Measurement
• Ferrograph image classification
• A matter of words: NLP for quality evaluation of Wikipedia medical articles
• FRI -- Feature Relevance Intervals for Interpretable and Interactive Data Exploration
• Automating Quality Assessment with NLP of LLM-Generated Defeaters
• Weighted Least Squares Twin Support Vector Machine with Fuzzy Rough Set Theory for Imbalanced Data Classification
• Does Adversarial Oversampling Help us?
• Multiclass Classification via Class-Weighted Nearest Neighbors
• Tackling Diverse Minorities in Imbalanced Classification
• Improving Performance of a Group of Classification Algorithms Using Resampling and Feature Selection
• MESS: Manifold Embedding Motivated Super Sampling
• A Deep-Learning Framework for Land-Sliding Classification from Remote Sensing Image
• Detection of Lying Electrical Vehicles in Charging Coordination Application Using Deep Learning
• ECG-ATK-GAN: Robustness against Adversarial Attacks on ECGs using Conditional Generative Adversarial Networks
• Dealing with Class Imbalance using Thresholding
• A Study imbalance handling by various data sampling methods in binary classification
• Improved Preterm Prediction Based on Optimized Synthetic Sampling of EHG Signal
• Generalized Constraints as A New Mathematical Problem in Artificial Intelligence: A Review and Perspective
• Trade-off between Bagging and Boosting for quantum separability-entanglement classification
• Cross-project Classification of Security-related Requirements
• Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks
• Predictors of Re-admission for Homeless Families in New York City: The Case of the Win Shelter Network
• Open Domain Suggestion Mining Leveraging Fine-Grained Analysis
• Accurate and Scalable Matching of Translators to Displaced Persons for Overcoming Language Barriers
• Misclassification cost-sensitive ensemble learning: A unifying framework
• Neighbor displacement-based enhanced synthetic oversampling for multiclass imbalanced data
• Domain-Aware Augmentations for Unsupervised Online General Continual Learning
• A Semi-Supervised Framework for Misinformation Detection
• EVAGAN: Evasion Generative Adversarial Network for Low Data Regimes
• Synthetic Sampling for Multi-Class Malignancy Prediction
• Defect prediction with bad smells in code
• Bridging Simulations and Observations: New Insights into Galaxy Formation Simulations via Out-of-Distribution Detection and Bayesian Model Comparison
• An Exploratory Study of COVID-19 Information on Twitter in the Greater Region
• Let's Predict Who Will Move to a New Job
• Statistical Analysis of Perspective Scores on Hate Speech Detection
• Minimizing the Societal Cost of Credit Card Fraud with Limited and Imbalanced Data
• Improved resection margins in breast-conserving surgery using Terahertz Pulsed imaging data
• A Neural Architecture for Detecting Confusion in Eye-tracking Data
• Deep Prediction of Investor Interest: a Supervised Clustering Approach
• Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach
• Collider phenomenology of new neutral scalars in a flavoured multi-Higgs model
• Investigating bankruptcy prediction models in the presence of extreme class imbalance and multiple stages of economy
• Effect of Imbalanced Datasets on Security of Industrial IoT Using Machine Learning
• Adaptive Class Weight based Dual Focal Loss for Improved Semantic Segmentation
• Class-dependent Compression of Deep Neural Networks
• Extending Machine Learning to Predict Unbalanced Physics Course Outcomes
• Prediction of the Facial Growth Direction is Challenging
• JaTeCS an open-source JAva TExt Categorization System
• Lexico-semantic and affective modelling of Spanish poetry: A semi-supervised learning approach
• Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems
• Proximity Matters: Analyzing the Role of Geographical Proximity in Shaping AI Research Collaborations
• Identifying Experts in Software Libraries and Frameworks among GitHub Users
• A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning
• SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts
• Socially Driven News Recommendation
• Classification of a New X-ray Catalog of Likely Counterparts to 4FGL-DR4 Unassociated Gamma-ray Sources Using a Neural Network
• Assessing the influence of social media feedback on traveler's future trip-planning behavior: A multi-model machine learning approach
• Hard-Aware Fashion Attribute Classification
• Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss
• What Can Be Predicted from Six Seconds of Driver Glances?
• Deep Learning Methods for Detecting Thermal Runaway Events in Battery Production Lines
• Identifying Radio Active Galactic Nuclei with Machine Learning and Large-Area Surveys
• A Glimpse of Physical Layer Decision Mechanisms: Facts, Challenges, and Remedies
• Classification Trees for Imbalanced and Sparse Data: Surface-to-Volume Regularization
• Multichannel LSTM-CNN for Telugu Technical Domain Identification
• A Minimax Probability Machine for Non-Decomposable Performance Measures
• Cross-Domain Evaluation of a Deep Learning-Based Type Inference System
• Characterizing Abhorrent, Misinformative, and Mistargeted Content on YouTube
• A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets
• Imbalanced classification: a paradigm-based review
• Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning
• BERT-based Chinese Text Classification for Emergency Domain with a Novel Loss Function
• Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers
• Understanding Human Context in 3D Scenes by Learning Spatial Affordances with Virtual Skeleton Models
• Meta-Learning for Resampling Recommendation Systems
• Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis
• PIE-ADA: Physics-Informed Ensemble with Adaptive Data Augmentation for Photometric Transient Classification
• A Method for Handling Multi-class Imbalanced Data by Geometry based Information Sampling and Class Prioritized Synthetic Data Generation (GICaPS)
• Affine-Invariant Robust Training
• As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning
• A Graph-based Stratified Sampling Methodology for the Analysis of (Underground) Forums
• Nonlinear Monte Carlo Method for Imbalanced Data Learning
• A Wavelet-CNN-LSTM Model for Tailings Pond Risk Prediction
• Learning Error-Driven Curriculum for Crowd Counting
• Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing
• Streamlining models with explanations in the learning loop
• Few-Shot Network Intrusion Detection Using Online Triplet Mining
• AI-Driven Predictive Maintenance with Environmental Context Integration for Connected Vehicles: Simulation, Benchmarking, and Field Validation
• Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data
• Classification of Fermi-LAT blazars with Bayesian neural networks
• ECG Heart-beat Classification Using Multimodal Image Fusion
• Predictive Modeling of Hospital Readmission: Challenges and Solutions
• The resilience of the sailboat stable region
• Segmented Federated Learning for Adaptive Intrusion Detection System
• Training Over-parameterized Models with Non-decomposable Objectives
• Hate Speech Detection in Clubhouse
• BiSTF: Bilateral-Branch Self-Training Framework for Semi-Supervised Large-scale Fine-Grained Recognition
• Taking Class Imbalance Into Account in Open Set Recognition Evaluation
• Equity-Directed Bootstrapping: Examples and Analysis
• FARF: A Fair and Adaptive Random Forests Classifier
• Predicting the Factuality of Reporting of News Media Using Observations About User Attention in Their YouTube Channels
• Man versus Machine: AutoML and Human Experts' Role in Phishing Detection
• Calibrating Class Activation Maps for Long-Tailed Visual Recognition
• Predicting the Effect of European Air Traffic on Cirrus Cloud Cover
• On-target Adaptation
• Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
• Predicting students' performance in online courses using multiple data sources
• A Novel Data-Driven Framework for Risk Characterization and Prediction from Electronic Medical Records: A Case Study of Renal Failure
• Good-Enough Example Extrapolation
• Astrophotometric search for massive stars in the Milky way. Confronting Random Forest predictions with available spectroscopy
• Iterative Nearest Neighborhood Oversampling in Semisupervised Learning from Imbalanced Data
• Predicting Loss Risks for B2B Tendering Processes
• Enhancing Control System Resilience for Airborne Wind Energy Systems Through Upset Condition Avoidance
• Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System
• Distance in Latent Space as Novelty Measure
• Proximity-Based Active Learning on Streaming Data: A Personalized Eating Moment Recognition
• Synthesizing Novel Pairs of Image and Text
• Understanding and Improving Usability of Data Dashboards for Simplified Privacy Control of Voice Assistant Data (Extended Version)
• High-Dimensional Data Set Simplification by Laplace-Beltrami Operator
• Using News Articles and Financial Data to predict the likelihood of bankruptcy
• Posture Recognition in the Critical Care Settings using Wearable Devices
• Lung Nodule Classification by the Combination of Fusion Classifier and Cascaded Convolutional Neural Networks
• ACDC: $\alpha$-Carving Decision Chain for Risk Stratification
• Time Series Classification Using Convolutional Neural Network On Imbalanced Datasets
• Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation
• Bond Default Prediction with Text Embeddings, Undersampling and Deep Learning
• On Predictive Explanation of Data Anomalies
• Semantic-based End-to-End Learning for Typhoon Intensity Prediction
• Spitzoid Lesions Diagnosis based on GA feature selection and Random Forest
• Envelope Imbalance Learning Algorithm based on Multilayer Fuzzy C-means Clustering and Minimum Interlayer discrepancy
• A Survey of Machine Learning Algorithms for Detecting Malware in IoT Firmware
• Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning
• Restrained Generative Adversarial Network against Overfitting in Numeric Data Augmentation
• A robust low data solution: dimension prediction of semiconductor nanorods
• Identification of complex mixtures for Raman spectroscopy using a novel scheme based on a new multi-label deep neural network
• Can We Detect Mastitis earlier than Farmers?
• Enhash: A Fast Streaming Algorithm For Concept Drift Detection
• Forecasting Probability of Default for Consumer Loan Management with Gaussian Mixture Models
• Modeling membrane curvature generation using mechanics and machine learning
• How to Better Distinguish Security Bug Reports (using Dual Hyperparameter Optimization
• Reduced Complexity Simulation of Wireless Sensor Networks for Application Development
• Comparative Analysis of CNN and Transformer Architectures with Heart Cycle Normalization for Automated Phonocardiogram Classification
• Feature reduction for machine learning on molecular features: The GeneScore
• Long-Tailed Learning for Generalized Category Discovery
• Data Requirement Goal Modeling for Machine Learning Systems
• Towards Quality Assurance of Software Product Lines with Adversarial Configurations
• Learning Test Traces
• Hellinger Distance Weighted Ensemble for Imbalanced Data Stream Classification
• Classification of Imbalanced Credit scoring data sets Based on Ensemble Method with the Weighted-Hybrid-Sampling
• Cache Bypassing for Machine Learning Algorithms
• Novel imaging revealing inner dynamics for cardiovascular waveform analysis via unsupervised manifold learning
• Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images
• Detecting Toxicity in News Articles: Application to Bulgarian
• Identification of Pediatric Sepsis Subphenotypes for Enhanced Machine Learning Predictive Performance: A Latent Profile Analysis
• Deep ensemble network with explicit complementary model for accuracy-balanced classification
• ICPR 2024 Competition on Rider Intention Prediction
• Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification
• A Two-Stage Variable Selection Approach for Correlated High Dimensional Predictors
• Adaptive Subspace Sampling for Class Imbalance Processing-Some clarifications, algorithm, and further investigation including applications to Brain Computer Interface
• CRCEN: A Generalized Cost-sensitive Neural Network Approach for Imbalanced Classification
• DropLoss for Long-Tail Instance Segmentation
• Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification
• Minority Class Oversampling for Tabular Data with Deep Generative Models
• The Threat to the Validity of Predictive Mutation Testing: The Impact of Uncovered Mutants
• Extração e Classificação de Características Radiômicas em Gliomas de Baixo Grau para Análise da Codeleção 1p/19q
• Unsupervised Severe Weather Detection Via Joint Representation Learning Over Textual and Weather Data
• AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection
• Predicting with limited data - Increasing the accuracy in VIS-NIR diffuse reflectance spectroscopy by SMOTE
• Machine learning, phase stability, and disorder with the Automatic Flow Framework for Materials Discovery
• Facial Expression Recognition using Deep Learning
• Deep Learning-based Stress Determinator for Mouse Psychiatric Analysis using Hippocampus Activity
• Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery
• Revisiting Method-Level Change Prediction: A Comparative Evaluation at Different Granularities
• Predicting the top and bottom ranks of billboard songs using Machine Learning
• Weak-supervision for Deep Representation Learning under Class Imbalance
• A Method for Discovering Novel Classes in Tabular Data
• Data models for service failure prediction in supply-chain networks
• MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities
• Emotion Classification: How Does an Automated System Compare to Naive Human Coders?
• An Analogy Based Method for Freight Forwarding Cost Estimation
• Distinguishing Between Roles of Football Players in Play-by-play Match Event Data
• Backdoor attacks on DNN and GBDT -- A Case Study from the insurance domain
• Learning-Based Relaxation of Completeness Requirements for Data Entry Forms
• Towards Stable Imbalanced Data Classification via Virtual Big Data Projection
• A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration
• Automatic Traceability Maintenance via Machine Learning Classification
• Dynamic Spectrum Matching with One-shot Learning
• Impact of normal lung volume choices on radiation pneumonitis risk prediction in locally advanced NSCLC radiotherapy
• Personalized Context-Aware Multi-Modal Transportation Recommendation
• Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning
• Imbalanced data preprocessing techniques utilizing local data characteristics
• Skyblocking for Entity Resolution
• Mimicking the halo-galaxy connection using machine learning
• The Relevance of Text and Speech Features in Automatic Non-native English Accent Identification
• k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks
• Predicting intraday jumps in stock prices using liquidity measures and technical indicators
• Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods
• Accelerometer-based Bed Occupancy Detection for Automatic, Non-invasive Long-term Cough Monitoring
• An Efficient Framework for Automated Screening of Clinically Significant Macular Edema
• Assessing Researcher Interdisciplinarity: A Case Study of the University of Hawaii NASA Astrobiology Institute
• Undersmoothing Causal Estimators with Generative Trees
• Investigating Limit Order Book Characteristics for Short Term Price Prediction: a Machine Learning Approach
• Supervised Sentiment Classification with CNNs for Diverse SE Datasets
• Public decision support for low population density areas: An imbalance-aware hyper-ensemble for spatio-temporal crime prediction
• Generating Synthetic Data with Locally Estimated Distributions for Disclosure Control
• Reformulating van Rijsbergen's $F_{\beta }$ metric for weighted binary cross-entropy
• Improving Slow Transfer Predictions: Generative Methods Compared
• Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey
• Orthogonal Activation with Implicit Group-Aware Bias Learning for Class Imbalance
• XClass: An Automated Multiwavelength Machine-Learning Pipeline for Classification of Extragalactic X-ray Sources. I. Pipeline Description
• Investigation into respiratory sound classification for an imbalanced data set using hybrid LSTM-KAN architectures
• Multi-Task Learning for Robot Perception with Imbalanced Data
• Hyperspectral data augmentation with transformer-based diffusion models
• On the Prediction of Wi-Fi Performance through Deep Learning
• DP-SMOTE: Integrating Differential Privacy and Oversampling Technique to Preserve Privacy in Smart Homes
• Classification of multivariate weakly-labelled time-series with attention
• Obstructive Sleep Apnea Characterization: A Multimodal Cross-Recurrence-Based Approach for Investigating Atrial Fibrillation
• Comparative Analysis of Deep Learning Architectures for Multi-Disease Classification of Single-Label Chest X-rays
• A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI
• Machine-Learned Dark Matter Subhalo Candidates in the 4FGL-DR2: Search for the Perturber of the GD-1 Stream
• Machine Learning Methods for Automated Interstellar Object Classification with LSST
• Graph Size-imbalanced Learning with Energy-guided Structural Smoothing
• Textual Analysis of Communications in COVID-19 Infected Community on Social Media
• Approaches to Improving the Accuracy of Machine Learning Models in Requirements Elicitation Techniques Selection