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ML
2002
ACM
167views Machine Learning» more  ML 2002»
14 years 9 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
CCS
2010
ACM
14 years 7 months ago
The limits of automatic OS fingerprint generation
Remote operating system fingerprinting relies on implementation differences between OSs to identify the specific variant executing on a remote host. Because these differences can ...
David W. Richardson, Steven D. Gribble, Tadayoshi ...
64
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KDD
2009
ACM
158views Data Mining» more  KDD 2009»
15 years 10 months ago
Feature shaping for linear SVM classifiers
: ? Feature Shaping for Linear SVM Classifiers George Forman, Martin Scholz, Shyamsundar Rajaram HP Laboratories HPL-2009-31R1 text classification machine learning, feature weighti...
George Forman, Martin Scholz, Shyamsundar Rajaram
TREC
2004
14 years 11 months ago
Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
14 years 9 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty