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FLAIRS
2008
13 years 11 months ago
On Using SVM and Kolmogorov Complexity for Spam Filtering
As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult t...
Sihem Belabbes, Gilles Richard
ICRA
2006
IEEE
100views Robotics» more  ICRA 2006»
14 years 3 months ago
Learning EMG Control of a Robotic Hand: Towards Active Prostheses
— We introduce a method based on support vector machines which can detect opening and closing actions of the human thumb, index finger, and other fingers recorded via surface E...
Sebastian Bitzer, P. Patrick van der Smagt
NIPS
2000
13 years 10 months ago
Feature Selection for SVMs
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This sear...
Jason Weston, Sayan Mukherjee, Olivier Chapelle, M...
TKDE
2008
123views more  TKDE 2008»
13 years 9 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
IDEAL
2005
Springer
14 years 2 months ago
Exploiting Sequence Dependencies in the Prediction of Peroxisomal Proteins
Prediction of peroxisomal matrix proteins generally depends on the presence of one of two distinct motifs at the end of the amino acid sequence. PTS1 peroxisomal proteins have a we...
Mark Wakabayashi, John Hawkins, Stefan Maetschke, ...