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...
—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...
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...
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...
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...