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ICML
2005
IEEE
14 years 8 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
AICS
2009
13 years 5 months ago
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
Frank G. Glavin, Michael G. Madden
EVOW
2004
Springer
14 years 1 months ago
Analysis of Proteomic Pattern Data for Cancer Detection
Abstract. In this paper we analyze two proteomic pattern datasets containing measurements from ovarian and prostate cancer samples. In particular, a linear and a quadratic support ...
Kees Jong, Elena Marchiori, Aad van der Vaart
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 11 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
ECML
2006
Springer
13 years 11 months ago
Evaluating Feature Selection for SVMs in High Dimensions
We perform a systematic evaluation of feature selection (FS) methods for support vector machines (SVMs) using simulated high-dimensional data (up to 5000 dimensions). Several findi...
Roland Nilsson, José M. Peña, Johan ...