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BMCBI
2010
130views more  BMCBI 2010»
13 years 9 months ago
The behaviour of random forest permutation-based variable importance measures under predictor correlation
Background: Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observ...
Kristin K. Nicodemus, James D. Malley, Carolin Str...
ICCV
2007
IEEE
14 years 10 months ago
Image Classification using Random Forests and Ferns
We explore the problem of classifying images by the object categories they contain in the case of a large number of object categories. To this end we combine three ingredients: (i...
Andrew Zisserman, Anna Bosch, Xavier Muñoz
ICIP
2009
IEEE
13 years 6 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
NIPS
2007
13 years 10 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
CVPR
2006
IEEE
14 years 10 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...