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» Ensembles of biased classifiers
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ALMOB
2008
69views more  ALMOB 2008»
14 years 11 months ago
Learning from positive examples when the negative class is undetermined- microRNA gene identification
Background: The application of machine learning to classification problems that depend only on positive examples is gaining attention in the computational biology community. We an...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
PAMI
2012
13 years 1 months ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
113
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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 4 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
CVPR
2004
IEEE
15 years 2 months ago
Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
15 years 2 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla