32 search results - page 1 / 7 » Using classifier ensembles to label spatially disjoint data |
INFFUS
2008
13 years 4 months ago
2008
act 11 We describe an ensemble approach to learning from arbitrarily partitioned data. The partitioning comes from the distributed process12 ing requirements of a large scale simul...
MCS
2005
Springer
13 years 10 months ago
2005
Springer
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
KDD
2001
ACM
14 years 4 months ago
2001
ACM
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
PCM
2007
Springer
13 years 10 months ago
2007
Springer
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
SDM
2010
SIAM
13 years 6 months ago
2010
SIAM
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...