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AAAI
2008
15 years 3 days ago
In-the-Dark Network Traffic Classification Using Support Vector Machines
This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
William H. Turkett Jr., Andrew V. Karode, Errin W....
INCDM
2010
Springer
308views Data Mining» more  INCDM 2010»
14 years 11 months ago
Data Mining with Neural Networks and Support Vector Machines Using the R/rminer Tool
We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs),...
Paulo Cortez
COLING
2002
14 years 9 months ago
Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...
Kengo Sato, Hiroaki Saito
FLAIRS
2001
14 years 11 months ago
Improvement of Nearest-Neighbor Classifiers via Support Vector Machines
Theoretically well-founded, Support Vector Machines (SVM)are well-knownto be suited for efficiently solving classification problems. Althoughimprovedgeneralization is the maingoal...
Marc Sebban, Richard Nock
BMCBI
2008
169views more  BMCBI 2008»
14 years 10 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...