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INFFUS
2008
60views more  INFFUS 2008»
14 years 9 months ago
Dynamic integration of classifiers for handling concept drift
Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunnin...
CBMS
2008
IEEE
14 years 11 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
ICPR
2008
IEEE
15 years 10 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
CORR
2008
Springer
140views Education» more  CORR 2008»
14 years 9 months ago
Adaptive Spam Detection Inspired by a Cross-Regulation Model of Immune Dynamics: A Study of Concept Drift
Abstract. This paper proposes a novel solution to spam detection inspired by a model of the adaptive immune system known as the crossregulation model. We report on the testing of a...
Alaa Abi-Haidar, Luis Mateus Rocha
MCS
2009
Springer
15 years 2 months ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar