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» Distance-based Disagreement Classifiers Combination
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IJCNN
2007
IEEE
13 years 11 months ago
Distance-based Disagreement Classifiers Combination
— We present a methodology to analyze Multiple Classifiers Systems (MCS) performance, using the diversity concept. The goal is to define an alternative approach to the convention...
Cinthia Obladen de Almendra Freitas, João M...
CIARP
2007
Springer
13 years 11 months ago
Confusion Matrix Disagreement for Multiple Classifiers
We present a methodology to analyze Multiple Classifiers Systems (MCS) performance, using the disagreement concept. The goal is to define an alternative approach to the conventiona...
Cinthia Obladen de Almendra Freitas, João M...
AI
2006
Springer
13 years 8 months ago
On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques
Abstract. We present a performance analysis of three linear dimensionality reduction techniques: Fisher's discriminant analysis (FDA), and two methods introduced recently base...
Mohammed Liakat Ali, Luis Rueda, Myriam Herrera
IPMU
2010
Springer
13 years 6 months ago
Using Uncertainty Information to Combine Soft Classifications
The classification of remote sensing images performed with different classifiers usually produces different results. The aim of this paper is to investigate whether the outputs of ...
Luisa M. S. Gonçalves, Cidália C. Fo...
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 8 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard