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SSPR
1998
Springer
15 years 4 months ago
Multi-interval Discretization Methods for Decision Tree Learning
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
Petra Perner, Sascha Trautzsch
IROS
2006
IEEE
107views Robotics» more  IROS 2006»
15 years 5 months ago
Heterogeneous and Hierarchical Cooperative Learning via Combining Decision Trees
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...
ECML
2005
Springer
15 years 5 months ago
Model Selection in Omnivariate Decision Trees
We propose an omnivariate decision tree architecture which contains univariate, multivariate linear or nonlinear nodes, matching the complexity of the node to the complexity of the...
Olcay Taner Yildiz, Ethem Alpaydin
JMLR
2010
108views more  JMLR 2010»
14 years 6 months ago
Tree Decomposition for Large-Scale SVM Problems
To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and train SVMs on the decomposed regions. Although the...
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen L...
BILDMED
2009
162views Algorithms» more  BILDMED 2009»
15 years 28 days ago
Extracting a Purely Non-rigid Deformation Field of a Single Structure
During endovascular aortic repair (EVAR) treatment, the aortic shape is subject to severe deformation that is imposed by medical instruments such as guide wires, catheters, and the...
Stefanie Demirci, Frode Manstad-Hulaas, Nassir Nav...