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» Diversified SVM Ensembles for Large Data Sets
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ICPR
2000
IEEE
15 years 10 months ago
Scaling-Up Support Vector Machines Using Boosting Algorithm
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
Dmitry Pavlov, Jianchang Mao, Byron Dom
DILS
2008
Springer
15 years 7 months ago
VisGenome and Ensembl: Usability of Integrated Genome Maps
It is not always clear how best to represent integrated data sets, and which application and database features allow a scientist to take best advantage of data coming from various ...
Joanna Jakubowska, Ela Hunt, John McClure, Matthew...
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 6 months ago
Model compression
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classif...
Cristian Bucila, Rich Caruana, Alexandru Niculescu...
MCS
2007
Springer
16 years 5 days ago
Stopping Criteria for Ensemble-Based Feature Selection
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
Terry Windeatt, Matthew Prior
KDD
2008
ACM
104views Data Mining» more  KDD 2008»
16 years 6 months ago
Learning methods for lung tumor markerless gating in image-guided radiotherapy
In an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. For gated lung cancer radiotherapy, it is difficult to generate ...
Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian ...