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MLDM
1999
Springer
13 years 12 months ago
Automatic Design of Multiple Classifier Systems by Unsupervised Learning
In the field of pattern recognition, multiple classifier systems based on the combination of the outputs of a set of different classifiers have been proposed as a method for the de...
Giorgio Giacinto, Fabio Roli
TFS
2011
194views Education» more  TFS 2011»
13 years 2 months ago
Top-Down Induction of Fuzzy Pattern Trees
Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structur...
R. Senge, Eyke Hüllermeier
MLMTA
2007
13 years 9 months ago
Consensus Based Ensembles of Soft Clusterings
— Cluster Ensembles is a framework for combining multiple partitionings obtained from separate clustering runs into a final consensus clustering. This framework has attracted mu...
Kunal Punera, Joydeep Ghosh
ESWA
2008
223views more  ESWA 2008»
13 years 7 months ago
Credit risk assessment with a multistage neural network ensemble learning approach
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the ...
Lean Yu, Shouyang Wang, Kin Keung Lai
IJCNN
2007
IEEE
14 years 1 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...