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INFFUS
2008
60views more  INFFUS 2008»
13 years 4 months ago
Dynamic integration of classifiers for handling concept drift
Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunnin...
CBMS
2008
IEEE
13 years 6 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
14 years 5 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»
13 years 4 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
13 years 9 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