Dimensional scalability of supervised and unsupervised concept drift detection: An empirical study

Jorge David Destephen Lavaire; Anshuman Singh; Mahmoud Yousef; Sumi Singh; Xiaodong Yue

doi:10.1109/BigData.2015.7364009

Dimensional scalability of supervised and unsupervised concept drift detection: An empirical study

Jorge David Destephen Lavaire, Anshuman Singh, Mahmoud Yousef, Sumi Singh, Xiaodong Yue

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	International Conference on Big Data
DOIs	https://doi.org/10.1109/BigData.2015.7364009
State	Published - Oct 1 2015
Externally published	Yes

Disciplines

Computer Sciences
Artificial Intelligence and Robotics

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10.1109/BigData.2015.7364009License: Unspecified

Cite this

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title = "Dimensional scalability of supervised and unsupervised concept drift detection: An empirical study",

author = "Lavaire, {Jorge David Destephen} and Anshuman Singh and Mahmoud Yousef and Sumi Singh and Xiaodong Yue",

note = "Big Data presents challenges for predictive analytic algorithms due to the possibility of non-stationary populations. Concept drift detection algorithms ca",

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T1 - Dimensional scalability of supervised and unsupervised concept drift detection: An empirical study

AU - Lavaire, Jorge David Destephen

AU - Singh, Anshuman

AU - Yousef, Mahmoud

AU - Singh, Sumi

AU - Yue, Xiaodong

N1 - Big Data presents challenges for predictive analytic algorithms due to the possibility of non-stationary populations. Concept drift detection algorithms ca

PY - 2015/10/1

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UR - https://ieeexplore.ieee.org/document/7364009

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DO - 10.1109/BigData.2015.7364009

M3 - Article

JO - International Conference on Big Data

JF - International Conference on Big Data

ER -

Dimensional scalability of supervised and unsupervised concept drift detection: An empirical study

Disciplines

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