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KDD
2005
ACM
117views Data Mining» more  KDD 2005»
15 years 10 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
14 years 4 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»
14 years 9 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
15 years 4 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»
14 years 9 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...