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» Unsupervised feature selection using a neuro-fuzzy approach
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BMCBI
2008
142views more  BMCBI 2008»
15 years 6 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...
CORR
2011
Springer
201views Education» more  CORR 2011»
14 years 10 months ago
On the Weakenesses of Correlation
The correlation of the result lists provided by search engines is fundamental and it has deep and multidisciplinary ramifications. Here, we present automatic and unsupervised met...
Paolo D'Alberto, Ali Dasdan
ECML
2007
Springer
16 years 21 days ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
IJCNN
2008
IEEE
16 years 28 days ago
Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
—In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) algor...
Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, Cunt...
MAMMO
2010
Springer
15 years 8 months ago
A Boosting Based Approach for Automatic Micro-calcification Detection
Abstract. In this paper we present a boosting based approach for automatic detection of micro-calcifications in mammographic images. Our proposal is based on using local features e...
Arnau Oliver, Albert Torrent, Meritxell Tortajada,...