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CSDA
2004
77views more  CSDA 2004»
13 years 7 months ago
Variable selection bias in regression trees with constant fits
The greedy search approach to variable selection in regression trees with constant fits is considered. At each node, the method usually compares the maximally selected statistic a...
Yu-Shan Shih, Hsin-Wen Tsai
ICIP
2005
IEEE
14 years 9 months ago
Motion-compensation using variable-size block-matching with binary partition trees
A new approach to Variable Size Block Matching is proposed, based on the binary partitioning of blocks. If a particular block does not allow for accurate motion compensation, then...
Marc Servais, Theodore Vlachos, Thomas Davies
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
14 years 8 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
ECML
2007
Springer
14 years 1 months ago
Decision Tree Instability and Active Learning
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
Kenneth Dwyer, Robert Holte
APPROX
2008
Springer
245views Algorithms» more  APPROX 2008»
13 years 9 months ago
Approximating Optimal Binary Decision Trees
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....
Micah Adler, Brent Heeringa