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» Ensembles of Classifiers from Spatially Disjoint Data
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PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
14 years 27 days ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
CEC
2010
IEEE
13 years 8 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
IPM
2002
106views more  IPM 2002»
13 years 7 months ago
A feature mining based approach for the classification of text documents into disjoint classes
This paper proposes a new approach for classifying text documents into two disjoint classes. The new approach is based on extracting patterns, in the form of two logical expressio...
Salvador Nieto Sánchez, Evangelos Triantaph...
AUSAI
2009
Springer
13 years 11 months ago
Ensemble Approach for the Classification of Imbalanced Data
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
KES
2007
Springer
14 years 1 months ago
Automated Ham Quality Classification Using Ensemble Unsupervised Mapping Models
This multidisciplinary study focuses on the application and comparison of several topology preserving mapping models upgraded with some classifier ensemble and boosting techniques ...
Bruno Baruque, Emilio Corchado, Hujun Yin, Jordi R...