A survey on concept drift adaptation

UCI Machine Learning Repository

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On Dynamic Feature Weighting for Feature Drifting Data Streams

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Time Series Forecasting in the Presence of Concept Drift: A PSO-based Approach

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Experimenting with prequential variations for data stream learning evaluation

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Is Artificial Intelligence Ready for Standardization?

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Multi-Stream Concept Drift Self-Adaptation Using Graph Neural Network

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Data-driven drift detection and diagnosis framework for predictive maintenance of heterogeneous production processes: Application to a multiple tapping process

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Concept drift robust adaptive novelty detection for data streams

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Adaptive online extreme learning machine by regulating forgetting factor by concept drift map

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SDDM: an interpretable statistical concept drift detection method for data streams

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Adaptive short-term wind power forecasting with concept drifts

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Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks

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Fast Reaction to Sudden Concept Drift in the Absence of Class Labels

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QuadCDD: A Quadruple-based Approach for Understanding Concept Drift in Data Streams

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Online Learning for Data Streams With Incomplete Features and Labels

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Tensor-Based Shot Boundary Detection in Video Streams

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HEAR: Fog-Enabled Energy-Aware Online Human Eating Activity Recognition

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Concept Drift Detection: Dealing With Missing Values via Fuzzy Distance Estimations

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ODIN

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The role of diversity and ensemble learning in credit card fraud detection

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Anomaly Detection and Concept Drift Adaptation for Dynamic Systems: A General Method with Practical Implementation Using an Industrial Collaborative Robot

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Model-centric transfer learning framework for concept drift detection

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Handling delayed labels in temporally evolving data streams

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On the Robustness of ML-Based Network Intrusion Detection Systems: An Adversarial and Distribution Shift Perspective

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A lightweight deep learning framework for transformer fault diagnosis in smart grids using multiple scale CNN features

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Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

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A differential evolution based method for tuning concept drift detectors in data streams

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: Dynamic clustering for tracking evolving environments

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Adaptive Ensemble Active Learning for Drifting Data Stream Mining

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Detecting virtual concept drift of regressors without ground truth values

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Machine Learning for Fraud Detection in E-Commerce: A Research Agenda

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VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streams

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Optimizing regression models for data streams with missing values

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A decision support framework for identifying novel ideas in new product development from cross-domain analysis

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Modeling recurring concepts in data streams: a graph-based framework

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Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes

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Online Machine Learning in Big Data Streams: Overview

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Marina : Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale

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Anomaly Detection Based on Isolation Mechanisms: A Survey

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A Novel Online and Non-Parametric Approach for Drift Detection in Big Data

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Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems

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On the Analysis and Improvement of Min-Entropy Estimation on Time-Varying Data

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Neural networks for online learning of non-stationary data streams: a review and application for smart grids flexibility improvement

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Novel hybrid pair recommendations based on a large-scale comparative study of concept drift detection

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Learning Parameter Distributions to Detect Concept Drift in Data Streams

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Addressing Event-Driven Concept Drift in Twitter Stream: A Stance Detection Application

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Learning from evolving data streams through ensembles of random patches

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A Taxonomy of Methods for Handling Data Streams in Presence of Concepts Drifts

Mittal, V., & Srivastava, R. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-4451-4_41

Learning under Concept Drift: A Review

Lu, J., Liu, A., Dong, F., Gu, F., Gama, J., & Zhang, G. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2876857 · Cited by 1,603

Adaptive online learning for classification under concept drift

Goel, K., & Batra, S. (2021) · International Journal of Computational Science and Engineering · doi:10.1504/ijcse.2021.115099 · Cited by 4

A systematic review on detection and adaptation of concept drift in streaming data using machine learning techniques

Arora, S., Rani, R., & Saxena, N. (2024) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1536 · Cited by 39

Algorithmes de machine learning adaptatifs pour flux de données sujets à des changements de concept

Loeffel, P.-X. (2017) · HAL · doi:10.70675/3b456eb5z117fz42a6z9436zb34bba3cfd1d