A learning framework for online class imbalance learning

No abstract is available for this paper.

• Publication year

  2013

• Venue

  IEEE Symposium on Computational Intelligence and Ensemble Learning

• Publication date

  2013-04-16

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1109/CIEL.2013.6613138
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Using Class Imbalance Learning for Software Defect Prediction

  2013cited by this paper
• Incremental Learning of Concept Drift from Streaming Imbalanced Data

  2013cited by this paper
• Multiclass Imbalance Problems: Analysis and Potential Solutions

  2012cited by this paper
• DDD: A New Ensemble Approach for Dealing with Concept Drift

  2012cited by this paper
• Ensemble diversity for class imbalance learning

  2011cited by this paper
• Online learning from imbalanced data streams

  2011cited by this paper
• Towards incremental learning of nonstationary imbalanced data stream: a multiple selectively recursive approach

  2011cited by this paper
• Negative correlation learning for classification ensembles

  2010cited by this paper
• MuSeRA: Multiple Selectively Recursive Approach towards imbalanced stream data mining

  2010cited by this paper
• The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift

  2010cited by this paper
• Ensemble-based classifiers

  2010cited by this paper
• The Effectiveness of a New Negative Correlation Learning Algorithm for Classification Ensembles

  2010cited by this paper
• Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC

  2010cited by this paper
• Adaptive Methods for Classification in Arbitrarily Imbalanced and Drifting Data Streams

  2009cited by this paper
• SERA: Selectively recursive approach towards nonstationary imbalanced stream data mining

  2009cited by this paper
• Mining Data Streams with Skewed Distribution by Static Classifier Ensemble

  2009cited by this paper
• Online learning from click data for sponsored search

  2008cited by this paper
• Classifying Data Streams with Skewed Class Distributions and Concept Drifts

  2008cited by this paper
• Detecting sudden concept drift with knowledge of human behavior

  2008cited by this paper
• A General Framework for Mining Concept-Drifting Data Streams with Skewed Distributions

  2007cited by this paper
• Early Drift Detection Method

  2005cited by this paper
• Online bagging and boosting

  2005influential reference
• Class imbalances versus small disjuncts

  2004cited by this paper
• Learning with Drift Detection

  2004cited by this paper
• Mining with rarity: a unifying framework

  2004cited by this paper
• A case-based technique for tracking concept drift in spam filtering

  2004cited by this paper
• A Multiple Resampling Method for Learning from Imbalanced Data Sets

  2004cited by this paper
• SMOTEBoost: Improving Prediction of the Minority Class in Boosting

  2003cited by this paper
• Online Learning of Non-stationary Sequences

  2003cited by this paper
• Mining concept-drifting data streams using ensemble classifiers

  2003cited by this paper
• SMOTE: Synthetic Minority Over-sampling Technique

  2002influential reference
• Prequential probability: principles and properties

  1999cited by this paper
• Addressing the Curse of Imbalanced Training Sets: One-Sided Selection

  1997influential reference
• Bagging Predictors

  1996cited by this paper
• A Novelty Detection Approach to Classification

  1995cited by this paper
• Ieee Transactions on Knowledge and Data Engineering 1 Relationships between Diversity of Classification Ensembles and Single-class Performance Measures

  year unknowncited by this paper
• Ieee Transactions on Knowledge and Data Engineering 1 Training Cost-sensitive Neural Networks with Methods Addressing the Class Imbalance Problem

  year unknowncited by this paper

• Multidimensional Self-Paced Ensemble for Imbalanced Data Streams with Concept Drift

  2026cites this paper
• Semi-Supervised Adaptive Learning for Streaming Data in Internet of Things Applications

  2026cites this paper
• Harmonized Gradient Descent for Class Imbalanced Data Stream Online Learning

  2025cites this paper
• BanglaDial: A merged and imbalanced text dataset for Bengali regional dialect analysis

  2025cites this paper
• Self-supervise ensemble for extreme imbalance data streams with concept drift

  2025cites this paper
• Adaptive Oversampling via Density Estimation for Online Imbalanced Classification

  2025cites this paper
• An online ensemble classification algorithm for multi-class imbalanced data stream

  2024influential citation
• A novel adaptive cost-sensitive convolution neural network based dynamic imbalanced fault diagnosis framework for manufacturing processes

  2024cites this paper
• Entropy-based dynamic ensemble classication algorithm for imbalanced data stream with concept drift

  2024cites this paper
• AOCBLS: A novel active and online learning system for ECG arrhythmia classification with less labeled samples

  2024cites this paper
• VMD-Based Ensembled SMOTEBoost for Imbalanced Multi-class Rotor Mass Imbalance Fault Detection and Diagnosis Under Industrial Noise

  2023cites this paper
• Preventing Discriminatory Decision-making in Evolving Data Streams

  2023cites this paper
• Online Ensemble of Ensemble OVA Framework for Class Evolution with Dominant Emerging Classes

  2023cites this paper
• Multiclass imbalanced and concept drift network traffic classification framework based on online active learning

  2023cites this paper
• Pro-IDD: Pareto-based ensemble for imbalanced and drifting data streams

  2023cites this paper
• An investigation of online and offline learning models for online Just-in-Time Software Defect Prediction

  2023influential citation
• Features and Classes Drift Detector to Deal with Imbalanced Data Streams

  2023cites this paper
• Online Harmonizing Gradient Descent for Imbalanced Data Streams One-Pass Classification

  2023influential citation
• A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification

  2022influential citation
• EFL Students’ Experience of Online Writing Class during Covid-19

  2022cites this paper
• Discrimination and Class Imbalance Aware Online Naive Bayes

  2022cites this paper
• Deterministic Sampling Classifier with weighted Bagging for drifted imbalanced data stream classification

  2022cites this paper
• A comparative study on online machine learning techniques for network traffic streams analysis

  2022cites this paper
• An extensive study of C-SMOTE, a Continuous Synthetic Minority Oversampling Technique for Evolving Data Streams

  2022cites this paper
• Learning from Class-imbalanced Data with a Model-Agnostic Framework for Machine Intelligent Diagnosis

  2021cites this paper
• Dynamic weighted majority based on over-sampling for imbalanced data streams

  2021cites this paper
• Online Fairness-Aware Learning with Imbalanced Data Streams

  2021influential citation
• Predict COVID-19 Spreading With C-SMOTE

  2021influential citation
• Dynamic weighted selective ensemble learning algorithm for imbalanced data streams

  2021cites this paper
• Learning in the Presence of Skew and Missing Labels Through Online Ensembles and Meta-reinforcement Learning

  2021cites this paper
• VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streams

  2021cites this paper
• Vulnerability exploitation time prediction: an integrated framework for dynamic imbalanced learning

  2021cites this paper
• The Atlas of Lane Changes: Investigating Location-Dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet

  2021cites this paper
• Online ensemble learning algorithm for imbalanced data stream

  2021cites this paper
• A comprehensive active learning method for multiclass imbalanced data streams with concept drift

  2021cites this paper
• A novel approach to maximize g-mean in nonstationary data with recurrent imbalance shifts

  2020cites this paper
• Sieve: An Ensemble Algorithm Using Global Consensus for Binary Classification

  2020cites this paper
• Class-Balanced Training for Deep Face Recognition

  2020cites this paper
• A Change Detector for Prior Probabilities of Classes

  2020cites this paper
• FABBOO - Online Fairness-Aware Learning Under Class Imbalance

  2020influential citation
• Online Learning With Adaptive Rebalancing in Nonstationary Environments

  2020influential citation
• Adaptive Online Learning for Vulnerability Exploitation Time Prediction

  2020cites this paper
• PWIDB: A framework for learning to classify imbalanced data streams with incremental data re-balancing technique

  2020cites this paper
• Two-Stage Game Strategy for Multiclass Imbalanced Data Online Prediction

  2020cites this paper
• Classification of Multi-class Imbalanced Data Streams Using a Dynamic Data-Balancing Technique

  2020cites this paper
• Rank-Based Chain-Mode Ensemble for Binary Classification

  2020cites this paper
• Performance Degradation of Multi-class Classification Model Due to Continuous Evolving Data Streams

  2020cites this paper
• C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams

  2020influential citation
• Robust Online Multilabel Learning Under Dynamic Changes in Data Distribution With Labels

  2020cites this paper
• Research on SDN intrusion detection based on online ensemble learning algorithm

  2020cites this paper
• Multi-class imbalanced semi-supervised learning from streams through online ensembles

  2020cites this paper
• Challenges in benchmarking stream learning algorithms with real-world data

  2020cites this paper
• Central-Diffused Instance Generation Method in Class Incremental Learning

  2019cites this paper
• Advances in imbalanced data learning

  2019cites this paper
• Adaptive Chunk-Based Dynamic Weighted Majority for Imbalanced Data Streams With Concept Drift

  2019cites this paper
• Human Activity Recognition in Smart Homes

  2019influential citation
• Cost-Sensitive Weighting and Imbalance-Reversed Bagging for Streaming Imbalanced and Concept Drifting in Electricity Pricing Classification

  2019cites this paper
• Change detection in human physical activities

  2018cites this paper
• SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

  2018influential citation
• Online Class Imbalance Learning for Quality Estimation in Manufacturing

  2018cites this paper
• Online Active Learning Paired Ensemble for Concept Drift and Class Imbalance

  2018cites this paper
• Learning Patterns from Imbalanced Evolving Data Streams

  2018cites this paper
• Learning from Imbalanced Data Streams

  2018cites this paper
• SCUT-DS: Methodologies for Learning in Imbalanced Data Streams

  2018cites this paper
• Improved Ensemble Methods to Solve Multi-class Imbalance Problem Using Adaptive Weights

  2018cites this paper
• Online learning for imbalanced data: optimizing asymmetric measures

  2018cites this paper
• Robust Text Mining in Online Social Network Context

  2018cites this paper
• Interpolation in the eXtended Classifier System: An architectural perspective

  2017cites this paper
• RARE CLASS PROBLEM IN DATA MINING: REVIEW

  2017cites this paper
• Learning from class-imbalanced data: Review of methods and applications

  2017cites this paper
• Evolutionary Cluster-Based Synthetic Oversampling Ensemble (ECO-Ensemble) for Imbalance Learning

  2017cites this paper
• On ensemble components selection in data streams scenario with reoccurring concept-drift

  2017cites this paper
• Gradual Class Evolution Detection Using Class Based Ensembles

  2017cites this paper
• Concept Drift Detection in Data Stream Mining : The Review of Contemporary Literature

  2017cites this paper
• Expert Systems With Applications

  2017cites this paper
• Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing

  2017cites this paper
• A streaming ensemble classifier with multi-class imbalance learning for activity recognition

  2017cites this paper
• A Systematic Study of Online Class Imbalance Learning With Concept Drift

  2017influential citation
• A Survey on Ensemble Learning for Data Stream Classification

  2017cites this paper
• Chapter 3 Relationships to Other Concepts

  2017cites this paper
• Online feature importance ranking based on sensitivity analysis

  2017cites this paper
• Concept Drift Detection with Hierarchical Hypothesis Testing

  2017cites this paper
• University of Birmingham Online Ensemble Learning of Data Streams with Gradually Evolved Classes

  2016cites this paper
• KNN-based dynamic query-driven sample rescaling strategy for class imbalance learning

  2016influential citation
• Device 1 Device 2 Device 3 Application Middleware Transport Internet ( Wireless ) Network Application Middleware Transport Internet Application Middleware Transport Internet

  2016cites this paper
• Concept Drift Adaptation in Large-scale Distributed Data Stream Processing

  2016cites this paper
• Exploring Social Relationships in Text Streams

  2016cites this paper
• Reference Architecture for Self-aware and Self-expressive Computing Systems

  2016cites this paper
• Change Point Detection Using Multivariate Exponentially Weighted Moving Average (MEWMA) for Optimal Parameter in Online Activity Monitoring

  2016cites this paper
• Self-aware Object Tracking in Multi-Camera Networks

  2016cites this paper
• Self-awareness and Self-expression: Inspiration from Psychology

  2016cites this paper
• A G-Means Update Ensemble Learning Approach for the Imbalanced Data Stream with Concept Drifts

  2016cites this paper
• Evolutionary Online Machine Learning from Imbalanced Data

  2016cites this paper
• Online Ensemble Learning of Data Streams with Gradually Evolved Classes

  2016cites this paper
• Dealing with Multiple Classes in Online Class Imbalance Learning

  2016influential citation
• Evolutionary model building under streaming data for classification tasks: opportunities and challenges

  2015cites this paper
• Concept drift detection for streaming data

  2015cites this paper
• Multi-window based ensemble learning for classification of imbalanced streaming data

  2015cites this paper
• Review on Class Imbalance Learning: Binary and Multiclass

  2015influential citation
• Concept Drift Detection for Imbalanced Stream Data

  2015cites this paper