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ICDAR
2007
IEEE
13 years 11 months ago
K-Nearest Oracle for Dynamic Ensemble Selection
For handwritten pattern recognition, multiple classifier system has been shown to be useful in improving recognition rates. One of the most important issues to optimize a multipl...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
DEXAW
1999
IEEE
97views Database» more  DEXAW 1999»
13 years 9 months ago
Mining Several Data Bases with an Ensemble of Classifiers
The results of knowledge discovery in databases could vary depending on the data mining method. There are several ways to select the most appropriate data mining method dynamicall...
Seppo Puuronen, Vagan Y. Terziyan, Alexander Logvi...
CBMS
2008
IEEE
13 years 7 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
ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
13 years 9 months ago
Arbiter Meta-Learning with Dynamic Selection of Classifiers and Its Experimental Investigation
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Alexey Tsymbal, Seppo Puuronen, Vagan Y. Terziyan
ICML
2002
IEEE
14 years 6 months ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko