Results 201 to 210 of about 336,769 (240)

RDDM: Reactive drift detection method

Expert Systems with Applications, 2017
Abstract Concept drift detectors are online learning software that mostly attempt to estimate the drift positions in data streams in order to modify the base classifier after these changes and improve accuracy. This is very important in applications such as the detection of anomalies in TCP/IP traffic and/or frauds in financial transactions.
Roberto S.M. Barros, Danilo R.L. Cabral, Paulo M. Gonçalves, Silas G.T.C. Santos   +3 more
openaire   +1 more source

Drift Detection Using Stream Volatility

2015
Current methods in data streams that detect concept drifts in the underlying distribution of data look at the distribution difference using statistical measures based on mean and variance. Existing methods are unable to proactively approximate the probability of a concept drift occurring and predict future drift points.
David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet   +3 more
openaire   +1 more source

Drift Detection and Correction Post-Tracking

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Accurate object tracking is a challenging problem due to numerous factors, that may cause the tracker to drift away from the target object. Typically, the output of a tracker is a bounding box (BB); such BB may not well discriminate the object from its background and may not be centered correctly around the object.
Tarek Ghoniemy, Maria A. Amer
openaire   +1 more source

Learning with Local Drift Detection

2006
Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem of learning when the distribution that generates the examples changes over time. We present a method for detection of changes in the probability distribution of examples.
João Gama, Gladys Castillo
openaire   +1 more source

Concept Drift Detection Delay Index

IEEE Transactions on Knowledge and Data Engineering, 2022
Anjin Liu, Jie Lu, Yiliao Song, Junyu Xuan, Guangquan Zhang   +4 more
openaire   +1 more source

DETECTION OF DISTRIBUTION DRIFT

Systems and Means of Informatics, 2022
openaire   +1 more source

Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Detecting topic drift

2009
Dan Knights, Mike Mozer, Nicolas Nicolov
openaire   +1 more source

Detecting ether drift

Physics Today, 1976
openaire   +1 more source

Neural Network Based Drift Detection

2023
Christofer Fellicious, Lorenz Wendlinger, Michael Granitzer   +2 more
openaire   +1 more source