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BMCBI
2006
201views more  BMCBI 2006»
15 years 4 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
117
Voted
IJON
2006
104views more  IJON 2006»
15 years 3 months ago
Kernel methods and the exponential family
The success of Support Vector Machine (SVM) gave rise to the development of a new class of theoretically elegant learning machines which use a central concept of kernels and the a...
Stéphane Canu, Alexander J. Smola
163
Voted
JMLR
2012
13 years 6 months ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
ACL
2004
15 years 5 months ago
Dependency Tree Kernels for Relation Extraction
We extend previous work on tree kernels to estimate the similarity between the dependency trees of sentences. Using this kernel within a Support Vector Machine, we detect and clas...
Aron Culotta, Jeffrey S. Sorensen
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
15 years 7 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi