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» Combining Methods for Dynamic Multiple Classifier Systems
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ICPR
2010
IEEE
15 years 4 months ago
Evolving Fuzzy Classifiers: Application to Incremental Learning of Handwritten Gesture Recognition Systems
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a...
Abdullah Almaksour, Eric Anquetil, Solen Quiniou, ...
ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
15 years 5 months ago
Dynamic Integration of Classifiers in the Space of Principal Components
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...
96
Voted
CVPR
2003
IEEE
16 years 2 months ago
Learning a discriminative classifier using shape context distances
For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, th...
Hao Zhang 0003, Jitendra Malik
104
Voted
EWCBR
2006
Springer
15 years 4 months ago
Combining Multiple Similarity Metrics Using a Multicriteria Approach
The design of a CBR system involves the use of similarity metrics. For many applications, various functions can be adopted to compare case features and to aggregate them into a glo...
Luc Lamontagne, Irène Abi-Zeid
PAMI
1998
127views more  PAMI 1998»
15 years 3 days ago
The Random Subspace Method for Constructing Decision Forests
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Tin Kam Ho