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» Evaluating algorithms that learn from data streams
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ICML
2002
IEEE
16 years 7 months ago
Pruning Improves Heuristic Search for Cost-Sensitive Learning
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Valentina Bayer Zubek, Thomas G. Dietterich
204
Voted
WCE
2007
15 years 8 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
FGCS
2007
99views more  FGCS 2007»
15 years 6 months ago
Mining performance data for metascheduling decision support in the Grid
: Metaschedulers in the Grid needs dynamic information to support their scheduling decisions. Job response time on computing resources, for instance, is such a performance metric. ...
Hui Li, David L. Groep, Lex Wolters
IJAMC
2008
99views more  IJAMC 2008»
15 years 6 months ago
Improving Educational Multimedia selection process using group decision support systems
Educational Multimedia (EMM) is becoming a mature and integral part of teaching and learning systems, mainly due to its ability improve teaching and learning. However, EMM selecti...
Mohammed N. A. Abdelhakim, Shervin Shirmohammadi
SIGIR
2005
ACM
16 years 11 days ago
Predicting query difficulty on the web by learning visual clues
We describe a method for predicting query difficulty in a precision-oriented web search task. Our approach uses visual features from retrieved surrogate document representations (...
Eric C. Jensen, Steven M. Beitzel, David A. Grossm...