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» Evolving kernels for support vector machine classification
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ICML
2004
IEEE
14 years 6 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
ML
2002
ACM
223views Machine Learning» more  ML 2002»
13 years 5 months ago
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
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...
Edda Leopold, Jörg Kindermann
SNPD
2004
13 years 6 months ago
Using extended phylogenetc profiles and support vector machines for protein family classification
We proposed a new approach to compare profiles when the correlations among attributes can be represented as a tree. To account for these correlations, the profile is extended with...
Kishore Narra, Li Liao
EVOW
2006
Springer
13 years 9 months ago
Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
Infection by the human papillomavirus (HPV) is associated with the development of cervical cancer. HPV can be classified to highand low-risk type according to its malignant potenti...
Sun Kim, Byoung-Tak Zhang
SIGKDD
2000
139views more  SIGKDD 2000»
13 years 5 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell