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» Sensitivity Analysis of the Result in Binary Decision Trees
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ISCIS
2009
Springer
13 years 11 months ago
Calculating the VC-dimension of decision trees
—We propose an exhaustive search algorithm that calculates the VC-dimension of univariate decision trees with binary features. The VC-dimension of the univariate decision tree wi...
Ozlem Asian, Olcay Taner Yildiz, Ethem Alpaydin
IDEAL
2000
Springer
13 years 10 months ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén
ECAI
2010
Springer
13 years 5 months ago
Describing the Result of a Classifier to the End-User: Geometric-based Sensitivity
This paper addresses the issue of supporting the end-user of a classifier, when it is used as a decision support system, to classify new cases. We consider several kinds of classif...
Isabelle Alvarez, Sophie Martin, Salma Mesmoudi
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
ECML
2005
Springer
14 years 14 days ago
Simple Test Strategies for Cost-Sensitive Decision Trees
We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...
Shengli Sheng, Charles X. Ling, Qiang Yang