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MLDM
1999
Springer
13 years 11 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
ICML
2008
IEEE
14 years 8 months ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 11 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
ICPR
2004
IEEE
14 years 8 months ago
Skin Detection: A Bayesian Network Approach
The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach...
Ira Cohen, Nicu Sebe, Theo Gevers, Thomas S. Huang
ICML
2004
IEEE
14 years 8 months ago
A MFoM learning approach to robust multiclass multi-label text categorization
We propose a multiclass (MC) classification approach to text categorization (TC). To fully take advantage of both positive and negative training examples, a maximal figure-of-meri...
Sheng Gao, Wen Wu, Chin-Hui Lee, Tat-Seng Chua