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» Data selection for support vector machine classifiers
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ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
15 years 2 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
ICML
2007
IEEE
15 years 10 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
SIGKDD
2000
139views more  SIGKDD 2000»
14 years 9 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
BIBM
2008
IEEE
137views Bioinformatics» more  BIBM 2008»
15 years 4 months ago
Exploring Alternative Splicing Features Using Support Vector Machines
Alternative splicing is a mechanism for generating different gene transcripts (called isoforms) from the same genomic sequence. Finding alternative splicing events experimentally ...
Jing Xia, Doina Caragea, Susan Brown
ECML
2006
Springer
15 years 1 months ago
Evaluating Feature Selection for SVMs in High Dimensions
We perform a systematic evaluation of feature selection (FS) methods for support vector machines (SVMs) using simulated high-dimensional data (up to 5000 dimensions). Several findi...
Roland Nilsson, José M. Peña, Johan ...