47 search results - page 1 / 10 » The effect of splitting on random forests |
ICIP
2009
IEEE
13 years 2 months ago
2009
IEEE
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
PAMI
1998
13 years 4 months ago
1998
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
IBPRIA
2007
Springer
13 years 8 months ago
2007
Springer
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...
SADM
2011
12 years 11 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...
ICMLA
2008
13 years 6 months ago
2008
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 ...