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PR
2010
158views more  PR 2010»
13 years 6 months ago
Out-of-bag estimation of the optimal sample size in bagging
The performance of m-out-of-n bagging with and without replacement in terms of the sampling ratio (m/n) is analyzed. Standard bagging uses resampling with replacement to generate ...
Gonzalo Martínez-Muñoz, Alberto Su&a...
PAKDD
2010
ACM
151views Data Mining» more  PAKDD 2010»
14 years 11 days ago
Ensemble Learning Based on Multi-Task Class Labels
Abstract. It is well known that diversity among component classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods achieve this goal through resam...
Qing Wang, Liang Zhang
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 8 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
ISVLSI
2003
IEEE
97views VLSI» more  ISVLSI 2003»
14 years 26 days ago
Q-Tree: A New Iterative Improvement Approach for Buffered Interconnect Optimization
The “chicken-egg” dilemma between VLSI interconnect timing optimization and delay calculation suggests an iterative approach. We separate interconnect timing transformation as...
Andrew B. Kahng, Bao Liu
BIBE
2005
IEEE
14 years 1 months ago
Diagnostic Rules Induced by an Ensemble Method for Childhood Leukemia
We introduce a new ensemble method based on decision tree to discover significant and diversified rules for subtype classification of childhood acute lymphoblastic leukemia, a ...
Jinyan Li, Huiqing Liu, Ling Li