Relationships between average depth and number of misclassifications for decision trees

Type
Article
Authors
Chikalov, Igor
Hussain, Shahid cc
Moshkov, Mikhail cc
KAUST Department
Applied Mathematics and Computational Science Program
Computational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
Office of the VP
Date
2014-02-14
Permanent link to this record
http://hdl.handle.net/10754/563398

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Abstract
This paper presents a new tool for the study of relationships between the total path length or the average depth and the number of misclassifications for decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [9] and datasets representing Boolean functions with 10 variables.
Publisher
IOS Press
Journal
Fundamenta Informaticae
DOI
10.3233/FI-2014-957
Collections
Articles; Applied Mathematics and Computational Science Program; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division