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» Support Vector Classification with Input Data Uncertainty
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IJCNN
2006
IEEE
14 years 1 months ago
SOM-Based Sparse Binary Encoding for AURA Classifier
—The AURA k-Nearest Neighbour classifier associates binary input and output vectors, forming a compact binary Correlation Matrix Memory (CMM). For a new input vector, matching ve...
Simon O'Keefe
DMIN
2009
132views Data Mining» more  DMIN 2009»
13 years 5 months ago
Understanding Support Vector Machine Classifications via a Recommender System-Like Approach
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...
BMCBI
2008
169views more  BMCBI 2008»
13 years 7 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
DAGM
2004
Springer
13 years 11 months ago
MinOver Revisited for Incremental Support-Vector-Classification
The well-known and very simple MinOver algorithm is reformulated for incremental support vector classification with and without kernels. A modified proof for its O(t-1/2 ) converge...
Thomas Martinetz
AAAI
2006
13 years 9 months ago
Multiclass Support Vector Machines for Articulatory Feature Classification
of somewhat abstracting away from the literal physiological measurements of articulation that are so closely tied to the acoustic signal, and with some additional computational bur...
Brian Hutchinson, Jianna Zhang