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University of Illinois at Urbana-Champaign
Instability of Decision Tree Classification Algorithms
Abstract
dc:descriptionEmpirical results illustrate that the trees constructed by the proposed algorithm are more stable, noise-tolerant, informative, expressive, and concise. The proposed sensitivity measure can be used as a metric to evaluate the stability of splitting predicates. The tree sensitivity is an indicator of the confidence level in rules and the effective lifetime of rules.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Li, Ruey-Hsia
- Contributors dc:contributor
-
- Belford, Geneva G.
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3023123
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81582