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» On the Noise Model of Support Vector Machines Regression
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ICANN
2007
Springer
14 years 3 months ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
AH
2004
Springer
14 years 2 months ago
Machine Learning Methods for One-Session Ahead Prediction of Accesses to Page Categories
This paper presents a comparison among several well-known machine learning techniques when they are used to carry out a one-session ahead prediction of page categories. We use reco...
José David Martín-Guerrero, Emili Ba...
TIT
2002
164views more  TIT 2002»
13 years 8 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 10 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
CSL
2008
Springer
13 years 9 months ago
A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Andreas Vlachos