Sciweavers

IPMU
2010
Springer
13 years 11 months ago
Attribute Value Selection Considering the Minimum Description Length Approach and Feature Granularity
Abstract. In this paper we introduce a new approach to automatic attribute and granularity selection for building optimum regression trees. The method is based on the minimum descr...
Kemal Ince, Frank Klawonn
CSDA
2007
148views more  CSDA 2007»
14 years 13 days ago
Classifying densities using functional regression trees: Applications in oceanology
The problem of building a regression tree is considered when the response variable is a probability density function. Splitting criteria which are well adapted to measure the diss...
David Nerini, Badih Ghattas
ENVSOFT
2006
125views more  ENVSOFT 2006»
14 years 14 days ago
Sensitivity analysis based on regional splits and regression trees (SARS-RT)
A global sensitivity analysis with regional properties is introduced. This method is demonstrated on two synthetic and one hydraulic example. It can be shown that an uncertainty a...
Florian Pappenberger, Ion Iorgulescu, Keith J. Bev...
CSDA
2008
120views more  CSDA 2008»
14 years 16 days ago
Tree-structured smooth transition regression models
ABSTRACT. This paper introduces a tree-based model that combines aspects of CART (Classification and Regression Trees) and STR (Smooth Transition Regression). The model is called t...
Joel Corrêa da Rosa, Alvaro Veiga, Marcelo C...
IJCAI
1993
14 years 1 months ago
Rule-Based Regression
While decision trees have been used primarily for classification, they can also model regression or function approximation. Like classification trees, regression trees often yield...
Sholom M. Weiss, Nitin Indurkhya
CSMR
2009
IEEE
14 years 5 months ago
Application of TreeNet in Predicting Object-Oriented Software Maintainability: A Comparative Study
There is an increasing interest in more accurate prediction of software maintainability in order to better manage and control software maintenance. Recently, TreeNet has been prop...
Mahmoud O. Elish, Karim O. Elish