711 search results - page 51 / 143 » Applying Support Vector Machines to Imbalanced Datasets |
PKDD
2009
Springer
14 years 3 months ago
2009
Springer
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
CORR
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced -- characteristics that are almost universal to modern dat...
MP
2011
13 years 4 months ago
2011
We propose a number of techniques for obtaining a global ranking from data that may be incomplete and imbalanced — characteristics that are almost universal to modern datasets co...
GECCO
2008
Springer
13 years 10 months ago
2008
Springer
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
KDD
2006
ACM
14 years 9 months ago
2006
ACM
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...