Results 91 to 100 of about 336,769 (240)

Driftage: a multi-agent system framework for concept drift detection. [PDF]

Gigascience, 2021
Vieira DM, Fernandes C, Lucena C, Lifschitz S.   +3 more
europepmc   +1 more source

Adversarial Attacks for Drift Detection

ESANN 2025 proceesdings
Concept drift refers to the change of data distributions over time. While drift poses a challenge for learning models, requiring their continual adaption, it is also relevant in system monitoring to detect malfunctions, system failures, and unexpected behavior. In the latter case, the robust and reliable detection of drifts is imperative.
Hinder, Fabian, Vaquet, Valerie, Hammer, Barbara   +2 more
openaire   +2 more sources

An Incremental Clustering Algorithm with Pattern Drift Detection for IoT-Enabled Smart Grid System. [PDF]

Sensors (Basel), 2021
Jiang Z, Lin R, Yang F.
europepmc   +1 more source

Roadmap of Concept Drift Adaptation in Data Stream Mining, Years Later

IEEE Access
As machine learning models are increasingly applied to real-world scenarios, it is essential to consider the possibility of changes in the data distribution over time.
Osama A. Mahdi, Nawfal Ali, Eric Pardede, Ammar Alazab, Tahsien Al-Quraishi, Bhagwan Das   +5 more
doaj   +1 more source

Analysis of Descriptors of Concept Drift and Their Impacts

Informatics
Concept drift, a phenomenon that can lead to degradation of classifier performance over time, is commonly addressed in the literature through detection and reaction strategies.
Albert Costa, Rafael Giusti, Eulanda M. dos Santos   +2 more
doaj   +1 more source

NASA CERES Spurious Calibration Drifts Corrected by Lunar Scans to Show the Sun Is not Increasing Global Warming and Allow Immediate CRF Detection [PDF]

, 2021
Grant Matthews
openalex   +1 more source

ECG Signal Processing using an Optimized Sliding Window Approach for Concept Drift Detection and Adaption

, 2023
Ketan Sanjay Desale, Swati Shinde
openalex   +1 more source

Trinity-Controller ADWIN: An Accuracy Guided Sensitivity Control Framework for Streaming Intrusion Detection

Journal of Information Systems and Informatics
Concept drift can severely undermine the reliability of streaming Intrusion Detection Systems (IDS), especially in realistic network traffic where changes are gradual, recurring, and often masked by noise and class imbalance.
Rodney Buang Sebopelo
doaj   +1 more source

The sensitivity of EGRET to gamma ray polarization [PDF]

A Monte Carlo simulation shows that EGRET (Energetic Gamma-Ray Experimental Telescope) does not even have sufficient sensitivity to detect 100 percent polarized gamma-rays. This is confirmed by analysis of calibration data. A Monte Carlo study shows that
Mattox, John R.
core   +1 more source

Detecting Concept Drift in Object Detection Models: A Collaborative AI-Human Approach for Defense Applications

IEEE Access
Concept drift, a persistent challenge in machine learning, can lead to the deterioration of model performance over time due to changes in data distribution. This is a pressing issue for the U.S.
Aiden M. Garcia-Rubio, Logan Heck, Kristin M. Schweitzer, Raymond M. Bateman, Adel Alaeddini, Krystel K. Castillo-Villar   +5 more
doaj   +1 more source