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KDD
2005
ACM
117views Data Mining» more  KDD 2005»
14 years 8 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
TSP
2010
13 years 2 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
PR
2006
102views more  PR 2006»
13 years 7 months ago
Prototype selection for dissimilarity-based classifiers
A conventional way to discriminate between objects represented by dissimilarities is the nearest neighbor method. A more efficient and sometimes a more accurate solution is offere...
Elzbieta Pekalska, Robert P. W. Duin, Pavel Pacl&i...
ICASSP
2008
IEEE
14 years 2 months ago
Deploying GOOG-411: Early lessons in data, measurement, and testing
We describe our early experience building and optimizing GOOG-411, a fully automated, voice-enabled, business finder. We show how taking an iterative approach to system developme...
Michiel Bacchiani, Françoise Beaufays, Joha...
INFORMS
1998
100views more  INFORMS 1998»
13 years 7 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...