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PR
2006
108views more  PR 2006»
15 years 4 months ago
Boosted discriminant projections for nearest neighbor classification
In this paper we introduce a new embedding technique to find the linear projection that best projects labeled data samples into a new space where the performance of a Nearest Neig...
David Masip, Jordi Vitrià
EDM
2009
120views Data Mining» more  EDM 2009»
15 years 2 months ago
Improving Student Question Classification
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to...
Cecily Heiner, Joseph L. Zachary
MICCAI
2003
Springer
16 years 5 months ago
An Automatic System for Classification of Nuclear Sclerosis from Slit-Lamp Photographs
A robust and automatic system has been developed to detect the visual axis and extract important feature landmarks from slit-lamp photographs, and objectively grade the severity of...
Shaohua Fan, Charles R. Dyer, Larry Hubbard, Barba...
ISTCS
1997
Springer
15 years 8 months ago
Learning with Queries Corrupted by Classification Noise
Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this ...
Jeffrey C. Jackson, Eli Shamir, Clara Shwartzman
HIS
2004
15 years 5 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...