504 search results - page 2 / 101 » Support Vector Classification with Input Data Uncertainty |
KDD
2000
ACM
13 years 8 months ago
2000
ACM
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
ML
2002
ACM
13 years 4 months ago
2002
ACM
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
SIAMREV
2010
12 years 11 months ago
2010
In this paper we propose and analyze a Stochastic-Collocation method to solve elliptic Partial Differential Equations with random coefficients and forcing terms (input data of the...
IJON
2008
13 years 4 months ago
2008
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...