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SADM
2011
13 years 2 months ago
Random survival forests for high-dimensional data
: 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...
Hemant Ishwaran, Udaya B. Kogalur, Xi Chen, Andy J...
ICMLA
2007
13 years 8 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
ICMLA
2008
13 years 8 months ago
Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous
Using decision trees that split on randomly selected attributes is one way to increase the diversity within an ensemble of decision trees. Another approach increases diversity by ...
Michael Gashler, Christophe G. Giraud-Carrier, Ton...
ECML
2007
Springer
13 years 11 months ago
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Anneleen Van Assche, Hendrik Blockeel
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
Detecting lateral gene transfers by statistical reconciliation of phylogenetic forests
Background: To understand the evolutionary role of Lateral Gene Transfer (LGT), accurate methods are needed to identify transferred genes and infer their timing of acquisition. Ph...
Sophie S. Abby, Eric Tannier, Manolo Gouy, Vincent...