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ICIP
2010
IEEE
13 years 8 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
ICMLA
2007
13 years 11 months ago
Estimating class probabilities in random forests
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
Henrik Boström
TDP
2010
124views more  TDP 2010»
13 years 8 months ago
Random Forests for Generating Partially Synthetic, Categorical Data
Abstract. Several national statistical agencies are now releasing partially synthetic, public use microdata. These comprise the units in the original database with sensitive or ide...
Gregory Caiola, Jerome P. Reiter
CATA
2009
13 years 11 months ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
ICASSP
2011
IEEE
13 years 1 months ago
Multi-cue based multi-target tracking using online random forests
Discriminative tracking has become popular tracking methods due to their descriptive power for foreground/background separation. Among these methods, online random forest is recen...
Xinchu Shi, Xiaoqin Zhang, Yang Liu, Weiming Hu, H...