144 search results - page 1 / 29 » Variable selection using random forests |
PRL
2010
13 years 5 months ago
2010
SADM
2011
13 years 1 months ago
2011
: Minimal depth is a dimensionless order statistic that measures the predictiveness of a variable in a survival tree. It can be used to select variables in high-dimensional problem...
BMCBI
2007
13 years 6 months ago
2007
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...
BMCBI
2006
13 years 6 months ago
2006
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
ESANN
2006
13 years 8 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...