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ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 7 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
13 years 5 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 ...
KDD
2009
ACM
158views Data Mining» more  KDD 2009»
14 years 8 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
13 years 8 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»
13 years 7 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