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An Overview on Concepts Drift Learning
(Ieee-inst Electrical Electronics Engineers Inc, 2019-01-01)
Concept drift techniques aim at learning patterns from data streams that may change over time. Although such behavior is not usually expected in controlled environments, real-world scenarios can face changes in the data, ...
A stable and online approach to detect concept drift in data streams
(Universidade de São Paulo - USPUniversidade Federal de São Carlos - UFSCarCentro de Robótica de São Carlos - CROBSociedade Brasileira de Computação - SBCSociedade Brasileira de Automática - SBASão Carlos, 2014-10)
The detection of concept drift allows to point out when a data stream changes its behavior over time, what supports further analysis to understand why the phenomenon represented by such data has changed. Nowadays, researchers ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift
(IEEE, 2012-01-01)
Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not ...
Avaliação criteriosa dos algoritmos de detecção de concept drifts
(Universidade Federal de PernambucoUFPEBrasilPrograma de Pos Graduacao em Ciencia da Computacao, 2016)
Fast unsupervised online drift detection using incremental Kolmogorov-Smirnov test
(Association for Computing Machinery - ACMSan Francisco, 2016-08)
Data stream research has grown rapidly over the last decade. Two major features distinguish data stream from batch learning: stream data are generated on the
y, possibly in a fast and variable rate; and the underlying ...
Measurements of electron drift velocity in isobutane using the pulsed townsend technique
(American Institute of Physics, 2014)