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» Image Classification using Random Forests and Ferns
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IBPRIA
2007
Springer
15 years 3 months ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu
ICPR
2010
IEEE
15 years 5 months ago
On-Line Random Naive Bayes for Tracking
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
DAGM
2008
Springer
15 years 1 months ago
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification
Three-dimensional electron-microscopic image stacks with almost isotropic resolution allow, for the first time, to determine the complete connection matrix of parts of the brain. I...
Björn Andres, Ullrich Köthe, Moritz Helm...
117
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ICMLA
2008
15 years 1 months ago
Calibrating Random Forests
When using the output of classifiers to calculate the expected utility of different alternatives in decision situations, the correctness of predicted class probabilities may be of...
Henrik Boström
BMCBI
2008
179views more  BMCBI 2008»
14 years 11 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao